Data Science

Data Science Jobs

648 jobs found

Today

Data Scientist III

Centene St. Louis, MO

St. Louis, MO

Today

$108k - $199k/yr Full time Advanced Analytics Artificial Intelligence Big Data

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Job Description

Centene is hiring a Data Scientist III for an onsite role in Missouri, supporting Ambetter membership forecasting and reporting. In this position, you will develop predictive models, analytic frameworks, and data products that support financial planning, pricing, and strategic decision-making while accounting for regulatory, competitive, operational, and product-level changes.

What you will do

Design and build data models that predict member outcomes or the future impact of key member decisions
Design, develop, validate, and maintain machine learning and statistical models, including forecasting methodologies for Marketplace membership and related business outcomes
Build and manage data assets, feature engineering pipelines, and analytical datasets that power forecasting and reporting
Perform exploratory analysis to spot emerging trends, structural market shifts, and business drivers that affect forecast performance
Design and construct analysis tools to extract and analyze data, and store analytical results in formats aligned to business needs
Conduct exploratory data analysis from complex data sources to create key datasets in support of Centene’s mission
Evaluate and design experiments to monitor key metrics and identify opportunities to improve outcomes
Develop mathematical and statistical models to identify relevant content or events and recognize patterns
Present research findings and communicate results of analysis
Contribute to automated, operational analytics processes that support scale and durability of analysis
Validate and measure health management program outcomes using SAS, R, and other tools, including provider, claims, and membership data
Manage multiple projects as assigned and help train Data Analysts
Support technical team liaisons across business requirements gathering, documentation, testing, delivery, and user adoption for Health Plan initiatives

Required qualifications

Authorization to work in the U.S. without employment-based visa sponsorship now or in the future
No sponsorship available, including H-1B, L-1, O-1, H-1B1, F-1, J-1, OPT, or CPT
Master’s degree in Statistics, Mathematics, Computer Science, Informatics, Econometrics, Engineering, or Experimental Science with 5+ years of experience, or a Bachelor’s degree with 7+ years of quantitative analysis experience in data science capabilities such as data mining, predictive modeling, machine learning, statistical modeling, large-scale data acquisition, transformation, and analysis of structured and unstructured data
Experience with database technologies including Teradata, MS SQL Server, and Snowflake

Preferred skills

R, Python, SQL, Databricks, Snowflake, Posit, and JupyterHub

Tools and technologies

R, Python, SQL
Databricks, Snowflake
Posit, JupyterHub
SAS, Teradata
MS SQL Server

Compensation and benefits

Competitive pay: USD 107,700 - 199,300 per year
Health insurance
401K and stock purchase plans
Tuition reimbursement
Paid time off plus holidays
Flexible approach to work with remote, hybrid, field, or office work schedules

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Today

Data Scientist

US Agricultural Marketing Service Little Rock, AR

Little Rock, AR

Today

$90k - $173k/yr Full time Azure Cloud Cloud Platform

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Job Description

Serve as a Data Scientist supporting critical mission systems through data management, pipeline automation, and analytics for operational and organizational insights.

Responsibilities

Develop data-driven solutions by converting raw structured or unstructured data into useful, actionable information for critical mission systems.
Design, build, and maintain scalable data pipelines using commercial cloud, open source, and/or custom software to process large datasets.
Implement data quality checks and procedures to maintain accuracy and consistency.
Create and apply data governance practices to manage data access, usage, and security across the organization.
Collaborate with teams to understand data needs, translate technical concepts, and align deliverables with business goals.
Convert analysis results into clear, actionable communications for Agency decision makers supporting data-driven decisions for programmatic and administrative functions.

Requirements

Degree: Bachelor’s degree in Mathematics, statistics, computer science, data science, or a field directly related to the position (at least at the baccalaureate level).
Or education + experience: Courses equivalent to a major field of study (30 semester hours), plus additional education or appropriate experience.
Citizenship: Must be a US Citizen or US National.
Selective Service: Individuals born male after 12/31/1959 must be Selective Service registered or exempt.
Background: Subject to satisfactory adjudication of background investigation and/or fingerprint check.
Probationary period: Successful completion of one-year probationary period unless previously served.
Direct Deposit: Required for Federal employees (per Public Law 104-134).
E-Verify: Successfully pass the E-Verify employment verification check.
MOU: Prior to an official offer, sign a memorandum of understanding acknowledging/accepting geographic mobility as a condition of employment.
Continuous Vetting: All USDA employees must be enrolled in Continuous Vetting.

Technologies

C++, Python, R, JavaScript, HTML, SQL
AWS, Azure, GCP

Duties by Grade Level

Full-performance level note: Duties listed are for the full-performance level; at developmental grade levels, assignments are more limited in scope, with less independence and limited complexity.
GS-12 level (examples):
- Assist in development of automated pipelines for data extraction from databases or publicly available sources to support statistical analysis, dataset construction, and data products (including spatial layers).
- Contribute to software packages or interactive data visualizations (dashboards or analytic tools) enabling data exploration across multiple subsets.
- Regularly use data science programming languages and related tooling, including C++/Python/R for statistical analysis; JavaScript/HTML for software or web application development; SQL for database management; and AWS/Azure/GCP for cloud platform work.
- Assist with development/implementation of statistical models relevant to ecological systems or disease surveillance, potentially including research articles, prototypes, or internal analytical products.
- Support research or software development projects, including communicating technical information to non-technical users and collaborating with teammates and end-users during iterative development.
- Note: No education substitution for this grade level.
GS-13 level (examples):
- Develop automated pipelines to extract data from databases or publicly available sources, combining data for statistical analysis, new database construction, and creation of data products with spatial layers for further analyses.
- Develop software packages and interactive data visualizations, including interactive dashboards and analytic tools, to visualize data in different subsets.
- Regularly use programming languages across multiple data science areas, including statistical data analysis (C++/Python/R), software/web development (JavaScript/HTML), database management (SQL), and/or cloud platforms (AWS/Azure/GCP).
- Develop statistical models of ecological systems, especially disease surveillance data, evidenced through authorship on research articles or software.
- Lead research or software development projects, communicating technical information orally and in writing to non-technical end-users and building developer/end-user relationships for collaborative development.
- Note: No education substitution for this grade level.

Benefits

Comprehensive benefits package (contact the hiring agency for details on specific benefits).

Who Can Apply

U.S. Citizens, Nationals, or those who owe allegiance to the U.S.
Federal employees whose job, agency, or department was eliminated and are eligible for priority over other applicants.

Additional Information

Applications accepted from any U.S. citizen.
Direct Hire Authority will be used to fill this position.
Veterans Preference and traditional rating and ranking of applicants do not apply due to the Direct Hire Authority for this vacancy.
Career Transition Assistance Plan (CTAP), Reemployment Priority List (RPL), or Interagency Career Transition Assistance Plan (ICTAP): see OPM website for how to apply.
Selection priority for CTAP/RPL/ICTAP candidates requires meeting basic eligibility requirements and all selective factors; CTAP/ICTAP candidates must be well qualified and receive a rating of at least 85/100 for selection priority.
First-time federal hires typically start at the lowest rate of the salary range for the selected grade.
Travel, transportation, and relocation expenses will not be paid.
Locality pay varies based on duty location.
Current AMS employees selected for this position remain in their current USDA office location or official duty station of record, except National Capital Region.
Promotion Potential: if selected for a position with further promotion potential, placement under a career development plan may enable non-competitive promotion if requirements are completed and management recommends.
Reasonable Accommodation (RA): RA requests may be submitted if a disability (covered by the Rehabilitation Act of 1973 as amended) interferes with completing USA Hire Competency Based Assessments.

Required Documents

Resume including personal information, education, detailed work experience related to major duties (with work schedule, hours worked per week, and dates), and title/series/grade (if applicable).
Resume must include supervisor name and phone number for each work period and whether supervisors may be contacted for reference checks.
Resume cannot exceed two pages; only one resume will be reviewed.
If education is required or used to qualify, submit a copy of college transcripts.
Applicants may provide documentation for veterans’ eligibility, although veterans’ preference does not apply under Direct Hire Authority.
For CTAP/RPL/ICTAP priority: proof of eligibility, SF-50 documenting separation (as applicable), last performance appraisal at least fully successful (or equivalent), and most recent SF-50 with position, grade level, and duty location.
Worker’s Compensation Separation: agency certification of inability to place employee AND notification of separation or Separation SF-50.
Disability Annuity Termination: notification from OPM of disability annuity termination AND Separation SF-50 of last position held.

How You Will Be Evaluated

Evaluated based on how well you meet the qualifications listed in the announcement and your application materials (resume, supporting documents), questionnaire responses, and required assessment responses.
Direct-Hire Authority: applicants who meet minimum qualifications (including specialized experience and selective placement factors, if applicable) will be referred to the selecting official.
A rating will not be used; veteran’s preference does not apply due to Direct Hire Authority.
USA Hire Assessment includes a cut score for required proficiency in critical general competencies: Attention to Detail; Customer Service; Decision Making; Flexibility; Integrity/Honesty; Interpersonal Skills; Learning; Reasoning; Self-Management; Stress Tolerance; Teamwork.
You must meet or exceed the cut score; you will not be considered if you score below it or fail to complete the assessment.

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Assistant Data Scientist

Colorado State University Fort Collins, CO

Fort Collins, CO

Today

$61k - $68k/yr Full time Arcgis Online Arcgis Pro Arcgis Survey 123

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Job Description

Support the National Park Service (NPS) Inventory and Monitoring Division by coordinating data lifecycle work at Colorado State University (CEMML).

Data visualization: create graphs and visualizations in R and Python, including dashboards
Metadata: author, update, and maintain metadata that describes data content and products
QA/QC: perform data quality assurance and quality control (data entry validation, data integrity checks, review, correction, and documentation)
Data packages: create and upload data packages and other products to the NPS DataStore repository
Data publication: develop scripts to generate EML metadata, machine-readable datasets, and reports using R, R Markdown, and Python
Relational databases: navigate, manage/maintain, and create relational databases
Workflow documentation: document and maintain data management workflows, manuals, instructional materials, scripts, user guides, and standard operating procedures
Team collaboration: contribute as a positive team member to network and divisional goals
Travel representation: represent NPS and CSU during work travel
Status updates: assist in preparing and delivering project status updates for NPS teams and communities

Requirements

Education: BS or BA degree
Relevant degree area: computer science, information technology, geographic information systems, geography, biology, ecology, environmental science, or related field
Programming: experience with R (statistical computing) or Python
Ecological data QA/QC: experience creating metadata, conducting QA/QC of ecological inventory and monitoring data, and documenting procedures to meet open data/open science requirements
Data visualization: experience creating data visualization and data dashboards
Communication: strong communication skills when working with external and internal partners

Tools & Technologies

R, Python, Power BI
AGOL dashboards, ArcGIS Survey 123, Field Maps
R Markdown, ESRI, EML metadata
NPS DataStore, Access, SQL Server
ArcGIS Pro, ArcGIS Online

Preferred Qualifications

One year of related work experience
Experience using and managing relational databases (Access, SQL Server)
Experience utilizing geospatial data and GIS (ArcGIS Pro and ArcGIS Online)
Experience working in natural resources or with ecological data
Demonstrated verbal and written communication skills to communicate and document workflow status and process
Demonstrated ability to ascertain the essence of an issue and collaborate with an interdisciplinary team of data managers, ecologists, and park staff
Self-motivated with acute attention to detail
Experience working in a collaborative environment
Experience working in a highly structured organization

Location

Onsite: Fort Collins, CO
This role supports several Southern networks and may be based in a listed location; indicate your preferred location during application.
Athens, GA
Lafayette, LA
Fort Collins, CO
Remote work may be an option in certain cases; share reasons during application.

Salary

USD 61,111 - 68,138 per year

Conditions of Employment

Pre-employment Criminal Background Check (required for new hires)
Required to complete a federal background investigation (NACI), adjudicated favorably to begin working
Must have a valid driver’s license or be able to obtain one by the employment start date
Legally authorized to work in the U.S. by the proposed start date; CEMML will not provide visa sponsorship for this position

Employment Details

Schedule: full-time, 40 hours/week
Estimated duration: approximately two years
May coordinate across 2-3 network offices

Required Application Documents

Cover letter
Resume/CV

Benefits

Colorado State University emphasizes community and contributions to teaching, research, and service

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Data Scientist - Decision Analytics

Payactiv, Inc. Milpitas, CA

Milpitas, CA

Today

$100k - $120k/yr Full time Analytics Artificial Intelligence Business Analytics

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Job Description

Payactiv, Inc. is looking for a Data Scientist to join the Decision Analytics team in Milpitas, CA, onsite. In this role, you will build end-to-end statistical and machine learning solutions that support forecasting, decisioning, risk, and analytics, working closely with stakeholders and engineering partners to deploy and monitor models and data pipelines.

What you’ll do

Own the full lifecycle of analytical solutions, spanning data exploration, feature engineering, model training and validation, deployment, and ongoing performance monitoring.
Develop and evaluate statistical and machine learning models, providing clear justification for methodology and model selection.
Write production-quality Python and SQL to work with multi-million-row datasets, with a focus on performance, accuracy, and reliability.
Convert ambiguous business questions into structured analyses and actionable recommendations for stakeholders.
Communicate analytical findings clearly, translating technical results into insights that inform business decisions.
Collaborate with data engineers on the design, validation, and maintenance of ETL processes and data pipelines to support data integrity, quality, and observability.
Keep current on emerging analytics, ML/AI, and cloud computing technologies, with strong advantage for familiarity with Snowflake and AWS SageMaker.

What you bring

Bachelor’s or Master’s degree in a quantitative discipline such as Data Science, Engineering, Statistics, Mathematics, Computer Science, Economics, etc.
1–3 years of experience in Data Science, Engineering, or a closely related role.
Proven proficiency in Python (pandas, NumPy, scikit-learn) and SQL, including data transformation, wrangling, and analysis on multi-million-row datasets.
Working knowledge of statistical modeling and machine learning fundamentals, including model selection trade-offs, data leakage, class imbalance, and validation methodology.
Hands-on experience across a range of modeling approaches, potentially including regression and generalized linear models, tree-based and ensemble methods, time series forecasting, clustering, or neural networks.
Solid understanding of relational databases, including writing performant queries, optimizing slow queries, and reasoning about schemas, joins, and query plans at production scale.
Ability to work independently and manage competing priorities with limited supervision.
Excellent communication skills for conveying complex findings to technical and non-technical audiences, with a proactive, curious, and detail-oriented mindset and strong problem-solving abilities.
Hands-on experience with business intelligence and visualization tools, including Sigma, Tableau, Looker, or Power BI.
Experience designing, validating, and maintaining ETL processes and data pipelines.

Technologies you may use

Python, pandas, NumPy, scikit-learn
SQL
Snowflake, AWS SageMaker
Sigma, Tableau, Looker, Power BI

Compensation and benefits

Salary range: USD 100,000–120,000 per year (based on experience) plus Bonus
Company sponsored Health, Dental, and Vision insurance
401K: traditional and Roth with a company match
Tuition Assistance or Tuition Reimbursement
Unlimited Paid Time off
Monthly Gym Reimbursement
Paid time off to volunteer
Paid Family Leave
Complimentary office lunches

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Staff Data Scientist, CRM & Lifecycle Marketing

Intuit Mountain View, CA

Mountain View, CA

Today

$194k - $263k/yr Full time Marketing A/B Testing Artificial Intelligence

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Job Description

Staff Data Scientist role on Intuit’s TurboTax CRM and Lifecycle Marketing data science team, focused on moving from campaign optimization to customer journey design.

Responsibilities

Shape Lifecycle Marketing strategy using data, including framing the right question before analysis is requested
Convert ambiguous marketing and product challenges into analytical frameworks, metric trees, and testable hypotheses that influence the CRM roadmap and resourcing
Partner with Tax leadership and Lifecycle Marketing to define north-star metrics, align on learning plans, and define success across the customer journey stages (re-engagement, start through completion, attach, and return the following year)
Apply causal measurement and counterfactual reasoning to identify what truly moved key outcomes, including campaign incrementality, journey-level lift, channel mix, halo, and retention
Design and run experiments, quasi-experiments, holdouts, and synthetic tests when clean A/B testing is not available
Act as a strategic data science partner across Marketing, Product, Data Engineering, Finance, and adjacent growth teams (paid acquisition, Credit Karma, in-product messaging)
Translate complex findings into actionable recommendations for Director- and VP-level stakeholders, and drive execution through the appropriate decision channel (Slack, readout, model, or working session)
Deliver insights at scale through analyses on journeys, audience segments, funnel and cohort performance, and lifetime value to pinpoint where CRM has the most leverage
Design segmentation and personalization approaches to improve targeting, reduce wasted volume, and free messaging capacity for high-value journeys
Build dashboards, visualizations, and self-serve tools, including GenAI-powered applications, enabling faster action from marketing and leadership
Identify, size, and prioritize AI use cases for CRM (personalization, journey orchestration, insight generation) based on business value, using evaluation frameworks to certify non-deterministic experiences (golden datasets, LLM-as-judge with human review, synthetic tests)
Create and maintain data products used by the business area and its agents, including prototyping data models, pipelines, and surfaces, then partnering with engineering to harden production-ready solutions
Automate recurring analytical bottlenecks into trusted agentic systems that stakeholders can run independently, with encoded business logic, monitoring, and clear guidance on what can run without a human in the loop
Champion data hygiene, instrumentation, and decision governance for CRM reporting and campaign measurement

Requirements

8+ years of experience in data science and analytics, with demonstrated ability to drive strategy and impact across a business area (CRM, lifecycle marketing, growth, retention, or equivalent); consumer subscription, fintech, or large-scale owned-channel marketing experience strongly preferred
Track record of first-principles thinking to translate ambiguous business strategy into analytical problems, including framing the question prior to analysis
Proven ability to design and interpret complex experiments beyond traditional A/B testing, and apply causal inference when experimentation is constrained (holdouts, quasi-experiments, incrementality; MMM or multi-touch attribution used as inputs, not substitutes, for causal claims)
Deep expertise in causal inference, customer segmentation, journey analytics, and experimentation design, with judgment to balance statistical rigor and business considerations
Experience building and owning predictive models through their lifecycle (classification, regression, propensity, or similar), accountable for decisions informed by the models
Experience creating reusable frameworks, methodologies, and data products that are adopted across the broader analytics and marketing community
Fluency in SQL and a statistical programming language (Python or R); experience partnering with engineering to harden pipelines, instrumentation, and production data products
Exceptional communication and stakeholder influence, including the ability to influence Director- and VP-level leaders across business and technical teams
Ability to operate effectively in a fast-paced, seasonal business with minimal guidance, making fast data-driven decisions across one-way vs. two-way door situations
Ability to use AI-native tools to plan, implement, and synthesize analyses across experiment readouts, quasi-experimental methods, revenue and retention deep dives, and measurement of journey or campaign launches
Comfort sizing AI use cases and evaluating non-deterministic systems, not limited to using AI for personal productivity
BS or MS in Statistics, Mathematics, Operations Research, Computer Science, Engineering, Econometrics, or a related field (advanced degree preferred)

Technologies

SQL
Python
R
GenAI
LLM-as-judge
A/B testing
MMM
Multi-touch attribution

Compensation

Salary: USD 194,000 - 262,500 per year

Benefits

Intuit provides a competitive compensation package with a strong pay for performance rewards approach
This position may be eligible for a cash bonus, equity rewards, and benefits, per applicable plans and programs

Location

Mountain View, CA (onsite)

Nice to Have

Hands-on experience with CRM platforms (e.g., Braze) and owned-channel measurement (email, push, SMS, in-app)
Experience designing journey-level measurement (behavioral milestones, coordinated intent) alongside campaign-level operational metrics
Familiarity with marketing mix models and multi-touch attribution, including when not to treat them as causal evidence

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Sr. Staff Data Scientist

Intuit Mountain View, CA

Mountain View, CA

Today

$211k - $285k/yr Full time Senior Analytics Data Analysis

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Job Description

Intuit is hiring a Senior Staff Data Scientist to help accelerate product growth through experimentation and deep analytics on the GBSG Product Growth team. This role is built around a data-driven, product-led approach, combining scalable growth loops, rigorous experimentation, and cross-functional collaboration to find the highest-impact opportunities across the product ecosystem.

As a senior individual contributor, you will partner with Product, Engineering, Design, and other teams to surface actionable insights and translate them into hypotheses that improve both customer outcomes and business performance. You will also champion analytical rigor and causal inference, while moving quickly from analysis to iterative execution.

What you’ll do

Contribute to and refine a data science roadmap focused on product funnel optimization and scalable growth initiatives.
Use causal inference, advanced statistical modeling, and machine learning techniques to turn complex data into actionable insights.
Build an integrated view of the customer journey across key business metrics, learning new areas quickly to identify growth opportunities.
Design, implement, and analyze targeted experiments to validate hypotheses with data-driven insights and sound causal analysis.
Collaborate with cross-functional partners to translate insights into strategic product enhancements.
Support ongoing improvements in instrumentation, data quality, and logging to strengthen analytical capabilities and understanding of customer behavior.
Act as a technical leader within the Product Growth team by championing analytical rigor and innovative problem-solving.
Mentor and share best practices in causal inference and advanced analytics to strengthen the team’s overall growth framework.
Rapidly assimilate diverse metrics and data sources to uncover insights and propose high-impact hypotheses.
Balance rigorous analysis with fast, iterative execution so insights move quickly into effective strategies.

What you bring

8+ years of experience in data science or analytics, with a proven record of using advanced analytical methods to drive product and business growth.
Demonstrated proficiency in causal inference, statistical modeling, machine learning, and experimental design.
Advanced skills in SQL, Python, R, plus experience using data visualization tools such as Tableau or Power BI to communicate insights.
Experience with data integration and pipeline development is a plus.
Strong ability to quickly understand new business areas and master essential data and metrics for decision-making.
Excellent communication and storytelling skills, with a track record of influencing technical and non-technical stakeholders through data-driven insights.
A customer-centric mindset with empathy and a commitment to uncover opportunities that improve customer experiences.
An agile, entrepreneurial approach that balances long-term strategic work with rapid experimentation.

Tools you’ll use

SQL, Python, R, Tableau, Power BI

Compensation and benefits

This position may be eligible for a cash bonus.
Equity rewards and benefits may be offered in line with applicable plans and programs.
Pay is based on job-related knowledge, skills, experience, and work location.
Intuit conducts regular comparisons across categories of ethnicity and gender for pay fairness.
Expected base pay range for Mountain View: USD 210,500 - 284,500 per year.

Location: Mountain View, CA (onsite)

Team focus: Global Business Solutions Group (GBSG) Product Growth, accelerating business outcomes using a data-driven, product-led approach.

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Senior Staff Data Scientist - Credit Karma Engagement

Intuit Charlotte, NC

Charlotte, NC

Today

$211k - $285k/yr Full time Senior Artificial Intelligence Causal Inference

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Job Description

Intuit is hiring a Senior Staff Data Scientist to support the Credit Karma Engagement workstream in Charlotte, North Carolina. In this onsite role, you will help shape the analytics vision for engagement and lifecycle initiatives, using experimentation and causal inference to improve long-term member retention.

What you’ll do

Set the data science strategy across Credit Karma engagement and lifecycle product initiatives, evaluating the member lifecycle end to end from activation and habit formation through retention, churn prevention, and reactivation.
Bring together analytics insights, business judgment, strategic considerations, and industry learnings to influence cross-functional leaders up to the VP level, serving as a connective point across Product, Marketing, Engineering, and Design.
Research and apply new ML and causal inference approaches, adapting external trends to engagement, lifecycle, and churn-prevention use cases while creating shareable frameworks that enable broader adoption within the business unit.
Build an iterative experimentation culture by designing complex studies including A/B/n, painted-door, bandits, and quasi-experimental designs, and by applying causal inference methods such as Propensity Score, DiD, and Synthetic Control when A/B testing is limited.
Connect learnings across a portfolio of experiments and analyses to identify patterns in member behavior, and develop durable segmentation strategies that strengthen targeting, personalization, and the in-product experience.
Partner with cross-functional teams to co-create the analytics and AI strategy for engagement and lifecycle, guiding phased testing and rollout with appropriate measurement, safety, risk, and ethical considerations while tying model performance metrics to member and business outcomes.
Mentor and elevate Data Scientists by setting scientific standards and best practices, contributing to calibrations and hiring, and scaling impact through delegation while staying hands-on in the highest-leverage areas.

Minimum qualifications

9+ years of experience in data science and analytics, with a demonstrated track record leading strategy and delivering impact across multiple initiatives or business units; experience in consumer product engagement, retention, or growth strongly preferred, with fintech experience a plus.
Experience in consumer platforms with membership-based or multi-product ecosystems where personalization and cross-product engagement drive long-term retention (preferred).
Ability to apply first-principles thinking to translate ambiguous business strategy into analytics problems at the business-unit level.
Proven ability to design and interpret complex experiments beyond traditional A/B testing and to apply causal inference when experimentation is constrained.
Deep expertise in causal inference, customer segmentation, and experimentation design, with judgment to balance statistical rigor and business considerations.
Experience with lightweight Machine Learning, including building offline classification and regression models to inform business decisions.
Experience creating reusable frameworks, methodologies, and toolkits adopted by a broader analytics community.
Strong communication and stakeholder influence, including the ability to influence Director- and VP-level leaders across business and technical groups.
Ability to work effectively in ambiguity with minimal guidance, make fast data-driven decisions (one-way vs. two-way door), and operate in a fast-paced environment.
Ability to use AI-native tools to plan, implement, and synthesize analyses across experiment readouts, quasi-experimental methodology, retention and churn deep dives, and measurement of feature launch success.
BS or MS in Statistics, Mathematics, Operations Research, Computer Science, Engineering, Econometrics, or a related field (advanced degree preferred).

Technologies

Machine Learning
Offline classification & regression models
AI-native tools
Propensity Score
DiD
Synthetic Control
A/B/n
Painted-door
Bandits
Quasi-experimental designs

Compensation

Intuit offers a competitive compensation package with a pay-for-performance rewards approach. This role may be eligible for a cash bonus, equity rewards, and benefits in accordance with applicable plans. Pay is based on job-related knowledge, skills, experience, and work location, and Intuit conducts regular pay comparisons across categories of ethnicity and gender. The expected base pay range for this position is USD 210,500 - 284,500 per year (noted with an expected base pay range shown as Oakland in the posting).