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65 jobs found

Today

Sr. Manager, Analytics Product Owner - Global Employer Services Technology Center

Deloitte Dallas, TX

Dallas, TX

Today

Full time Manager AI Enablement Ai Workflows

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Job Description

Deloitte's Global Employer Services Technology Center in Dallas seeks a Sr. Manager to steer the analytics product portfolio, shaping strategy and delivering data-driven solutions. The role blends leadership of analytics teams with close collaboration across stakeholders to realize measurable business value through advanced analytics, GenAI, BI, and AI-enabled insights. This position operates in a hybrid environment and requires close coordination with US Tax professionals in person several days per week.

Responsibilities

Lead the Global Employer Services Analytics strategy and roadmap, prioritizing investments across machine learning, GenAI, agentic AI, business intelligence, and dashboards based on business outcomes, adoption, ROI, and value realization.
Direct ideation, prototyping, and delivery of analytics innovations and products, incorporating market, client, and stakeholder feedback to scale solutions and ensure business adoption.
Provide hands-on leadership to analytics teams and cross-functional partners, owning priorities, timelines, delivery quality, and execution discipline while coaching talent and partnering with Global Technology and senior stakeholders.

Requirements

Ability to perform job responsibilities within a hybrid work model that requires US Tax professionals to co-locate in person 2 - 3 days per week
Bachelor's degree in Computer Science, Information Systems, Data Management, or a related field
8+ years of progressive experience in analytics, data, or a related field
Experience leading teams of up to 20 analytics professionals
Proven experience with at least one advanced analytics method such as predictive analytics, recommendation engines, optimization algorithms, segmentation, or forecasting
Successful experience with at least one analytics visualization platform such as Qlik, Power BI, Tableau, or ThoughtSpot
Limited immigration sponsorship may be available
One of the following accreditations obtained:
- Licensed CPA in state of practice/primary office if eligible to sit for the CPA
- AWS Certified Solutions Architect
- Microsoft Azure
- Certified Secure Software Lifecycle Professional (CSSLP)
- CISSP (Certified Information Systems Security Professional)
- Certified in Risk and Information Systems Controls (CRISC)
- Alteryx Designer- Advanced Certification
- IASA's Certified IT Architect (CITA) (F/A Level)
- Open Group Certified Architect (Open CA)
- Certified SAFe® DevOps Practitioner
- Six Sigma Green/Black Belt

Technologies

Qlik
Power BI
Tableau
ThoughtSpot
Python
AWS
Alteryx Designer
GenAI
RAG
Agentic AI

Benefits

Discretionary annual incentive program eligibility

Qualifications

Ability to perform job responsibilities within a hybrid work model that requires US Tax professionals to co-locate in person 2 - 3 days per week
Bachelor's degree in Computer Science, Information Systems, Data Management, or a related field
8+ years of progressive experience in analytics, data, or a related field
Experience leading teams of up to 20 analytics professionals
Proven experience with at least one advanced analytics method such as predictive analytics, recommendation engines, optimization algorithms, segmentation, or forecasting
Successful experience with at least one analytics visualization platform such as Qlik, Power BI, Tableau, or ThoughtSpot
Limited immigration sponsorship may be available
One of the following accreditations obtained:
- Licensed CPA in state of practice/primary office if eligible to sit for the CPA
- AWS Certified Solutions Architect
- Microsoft Azure
- Certified Secure Software Lifecycle Professional (CSSLP)
- CISSP (Certified Information Systems Security Professional)
- Certified in Risk and Information Systems Controls (CRISC)
- Alteryx Designer- Advanced Certification
- IASA's Certified IT Architect (CITA) (F/A Level)
- Open Group Certified Architect (Open CA)
- Certified SAFe® DevOps Practitioner
- Six Sigma Green/Black Belt

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Today

Secure AI Engineer Manager

Accenture Atlanta, GA

Atlanta, GA

Today

$87k - $294k/yr Full time Manager Ai Security Artificial Intelligence

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Job Description

Accenture is seeking a Secure AI Engineer Manager for onsite work in Atlanta, GA, with a salary range of USD 87,400 to 293,800 per year.

Responsibilities

Deliver cybersecurity focused secure AI solutions that enhance enterprise AI adoption while safeguarding AI-enabled operations.
Design, set up, and test prototype and production secure AI deployment solutions, ensuring smooth integration of all components.
Collaborate with project teams, team leads, delivery leads, and client stakeholders to create standout AI Security and Governance offerings powered by LLM platforms, frontier-grade models, agentic frameworks, and AI/MCP gateways, including Anthropic Claude, OpenAI, and Azure OpenAI.
Build strong client relationships and earn the trust of key advisors.
Present the business case for the most effective secure AI solution recommended to the client.
Contribute to Accenture sales efforts when needed.
Continue to develop foundational AI, AI security, emerging technologies, and business expertise.

Requirements

Minimum 5 years of total experience in cybersecurity with depth in at least one area such as AppSec, SecOps/detection engineering, IAM, cloud security, offensive security/penetration testing, GRC, or responsible AI.
Minimum 1 year of hands-on experience with agentic coding tools such as Claude Code, Cursor, GitHub Copilot, or Codex, with active daily use.
Minimum 1 year of experience in AI architecture fundamentals, including LLMs, agentic systems, A2A, RAG, MLOps pipelines, MCP, AI Gateway, and model serving.
Minimum 1 year of experience in AI specific security topics, including OWASP LLM Top 10, prompt injection, adversarial inputs, and AI supply chain risks.
Minimum 1 year of experience in threat modeling for AI systems (STRIDE, PASTA, or equivalent) applied to LLM deployments and agentic pipelines.
Cloud platform security fundamentals certification (AWS, Azure, or GCP).
Bachelor's degree or equivalent work experience (minimum 12 years). If holding an Associate’s Degree, a minimum of 6 years of work experience is required.

Technologies

Anthropic Claude
OpenAI
Azure OpenAI
Claude Code
Cursor
GitHub Copilot
Codex

Benefits

Medical coverage
Dental coverage
Vision coverage
Life insurance
Long-term disability coverage
401(k) plan
Bonus opportunities
Paid holidays
Paid time off

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1d ago

Sr Databricks Data Engineer

Deloitte New York, NY

New York, NY

1d ago

$116k - $229k/yr Full time Manager Big Data Bigdata

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Job Description

Deloitte is seeking a Sr Databricks Data Engineer in New York, NY (onsite), with a salary range of USD 116,200 - 229,100 per year, to design and optimize cloud-based data engineering solutions on Databricks for analytics and AI use cases across enterprise data platforms.

Responsibilities

Define, document, and promote best-in-class approaches for data architecture, integration, and modelling.
Design, build, and maintain robust data pipelines and architectures that support large-scale enterprise data needs.
Initiate and manage efforts to improve data quality, operational efficiency, and process scalability.
Evaluate, pilot, and adopt new big data and analytics technologies; lead, coach, and develop teams of data engineers and architects to ensure project success.
Consult on and implement governance, security, and compliance strategies tailored to modern cloud data ecosystems.
Explain technical concepts and business value to executives, business leads, and technology teams.
Oversee CI/CD practices and automation using tools such as Azure DevOps, AWS Code Pipeline, Jenkins, TFS, or PowerShell for streamlined deployments and operations.

Requirements

Minimum 1 year of relevant experience
Bachelor's degree in Computer Science, Engineering, or a related field
Ability to work independently and as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Capability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeanor
Ability to meet deadlines

Technologies

Databricks
Delta Lake
Apache Spark
PySpark
Delta Live Tables
Autoloader
Structured Streaming
Databricks Workflows
Unity Catalog
Apache Airflow
CI/CD pipelines
Azure DevOps
AWS Code Pipeline
Jenkins
TFS
PowerShell
AWS
Azure
GCP
Databricks Lakeflow

Benefits

Discretionary annual incentive program

The Team

Deloitte's Core AI & Data practice helps organizations modernize data platforms, strengthen enterprise data foundations, and scale analytics and artificial intelligence capabilities across the business. The team works with clients to architect, engineer, and deploy cloud-based data solutions that improve decision-making, enable innovation, and support large-scale transformation. Practitioners collaborate across business and technology functions to solve complex challenges in data modernization.

Preferred qualifications

Master's degree in Computer Science, Engineering, or a related field
Experience in one or more AWS, Azure, and GCP cloud ecosystems and related big data services
Experience tuning and optimizing performance in Databricks and Apache Spark environments
Experience with Databricks Lakeflow
Experience with artificial intelligence and machine learning solutions

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2d ago

Director, Data Scientist - External Data Strategy

Capital One New York, NY

New York, NY

2d ago

$294k - $335k/yr Full time Manager Big Data Cloud Platform

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Job Description

Capital One offers the Director of Data Scientist - External Data Strategy role in New York, NY (onsite), with a salary range of USD 293,600 - 335,100 per yearly.

Responsibilities

Collaborate with data scientists, software engineers, and product managers to deliver data and insights that drive business decisions.
Apply a broad tech stack including Python, Conda, AWS, Databricks, Spark, and related tools to extract actionable insights from large data volumes.
Develop machine learning models and end-to-end data pipelines, covering design, training, evaluation, validation, and deployment.
Develop deep subject matter expertise in consumer financial data to support Capital One's customer-focused decisions.
Manage a team of 10-15 data scientists, setting strategic direction, providing technical mentorship, and developing both individual contributors and managers.
Translate complex analytical work into clear, tangible business goals through effective communication.

Requirements

Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) plus 9 years of data analytics experience.
Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) or MBA with a quantitative concentration plus 7 years of data analytics experience.
PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) plus 4 years of data analytics experience.
At least 4 years of experience leveraging open source programming languages for large-scale data analysis.
At least 4 years of experience working with machine learning.
At least 4 years of experience utilizing relational databases.

Technologies

Python
Conda
AWS
Databricks
Spark
SQL

Benefits

Health benefits
Financial benefits
Incentives (cash bonuses and/or long-term incentives)

The ideal candidate is

Customer first. Prioritizes decisions that benefit customers and balances analytical rigor with practical outcomes.
A leader. Challenges conventional thinking, collaborates with stakeholders, and cultivates talent within the team and beyond.
Technical. Hands-on with open-source tools and cloud platforms, eager to deepen expertise.
A data guru. Comfortable with big data, capable of retrieving, combining, and analyzing data from diverse sources and structures, with a focus on understanding data to drive results.

Preferred qualifications

At least 3 years of experience working with AWS
At least 3 years of experience managing people
At least 5 years of experience in Python for large-scale data analysis
At least 5 years of experience with machine learning
At least 5 years of experience with Spark

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3d ago

Senior Manager, Data Scientist - US Card (Generative AI Systems)

Information Technology Senior Management Forum McLean, VA

McLean, VA

3d ago

$225k - $257k/yr Full time Manager Ai Ml Artificial Intelligence

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Job Description

Senior Manager, Data Scientist - US Card (Generative AI Systems) on the Genesis team focuses on building and operating generative AI based data science solutions and ML driven products across the card business, with cross functional leadership and a broad tech stack.

Responsibilities

Collaborate with a cross functional team of data scientists, software engineers, and product managers to deliver a product customers love
Utilize a broad technology stack including Python, Kubernetes, AWS, H2O, Spark, and more to uncover insights from large volumes of numeric and textual data
Develop machine learning models through all stages of the lifecycle from design through training, evaluation, validation, and deployment
Translate the complexity of technical work into clear, actionable business objectives through strong interpersonal communication

Requirements

Either a Bachelor's degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) with 7+ years of data analytics experience, or a Master's degree in a quantitative field with the degree expected by the start date
At least 2 years of experience using open source programming languages for large scale data analysis
At least 2 years of experience applying machine learning
At least 2 years of experience working with relational databases

Technologies

Python
Kubernetes
AWS
H2O
Spark

Benefits

Health benefits
Financial benefits (incentives, cash bonuses, long-term incentives)
Inclusive set of health, financial and other benefits that support total well-being

Description

Data sits at the core of everything we do. Our early disruption of the credit card market came from personalizing offers through statistical modeling and relational databases, a move that helped launch a Fortune 200 company famed for data-driven decision making. As a Data Scientist on the Genesis team, you will join a group shaping the next wave of disruption at scale, working with cutting edge computing and ML technologies across billions of customer records to unlock opportunities that help people save time and money in their financial lives.

Team

The Generative AI Systems (Genesis) team within Card Data Science builds state-of-the-art generative AI solutions for dialogue, text summarization, reading comprehension, speech recognition, image and document processing, as well as time-series sequencing modeling. We partner with product, technology and design teams to deliver internal tools that improve efficiency for data analytics and business operations, as well as customer-facing applications that enhance the user experience.

Role Description

Partner with a cross functional team of data scientists, software engineers, and product managers to deliver a product customers love
Leverage a broad stack of technologies — Python, Kubernetes, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
Flex your interpersonal skills to translate the complexity of your work into tangible business goals

Qualifications

Basic qualifications

Either a Bachelor's degree in a quantitative field with 7+ years of data analytics experience or a Master's degree in a quantitative field with the degree expected by the start date
At least 2 years of experience using open source programming languages for large-scale data analysis
At least 2 years of experience applying machine learning
At least 2 years of experience working with relational databases

Preferred qualifications

PhD in a STEM field plus 4 years of data analytics experience
At least 1 year of AWS experience
At least 1 year of people management experience
At least 5 years of experience in Python, Scala, or R for large-scale data analysis
At least 5 years of experience with machine learning

Type: Full-time

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3d ago

AI Engineer, Manager - Tax Transformation

Deloitte Philadelphia, PA

Philadelphia, PA

3d ago

$128k - $262k/yr Full time Backend Developer Manager Artificial Intelligence

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Job Description

Deloitte, Philadelphia, PA with a hybrid work model is seeking an AI Engineer, Manager - Tax Transformation to oversee the design, development, deployment, and support of custom AI applications and modules, lead a team of engineers, drive project execution, manage stakeholder communications, and ensure high-quality deliverables aligned with organizational objectives.

Responsibilities

Define and enforce best practices and coding standards across the project lifecycle.
Conduct thorough code reviews to maintain high quality and adherence to guidelines.
Work independently and in close collaboration with the team to drive delivery.
Communicate clear instructions to team members and help manage day-to-day operations.
Maintain regular communication with the client to align expectations and progress.
Design, develop, and maintain robust and scalable Python applications.
Write clean, maintainable, and efficient code following industry standards.
Optimize code for performance and scalability to ensure efficient data handling.
Collaborate with cross-functional teams to deliver high-quality software solutions.
Identify and resolve technical issues to ensure reliability and performance of applications.
Create and maintain comprehensive documentation for code, processes, and workflows.
Provide guidance and mentorship to junior developers, fostering a collaborative and productive team environment.

Requirements

Hybrid work model requiring US Tax professionals to co-locate in person 2-3 days per week.
Bachelor's degree in computer science, engineering, or a related discipline.
5+ years of development experience with a track record designing, developing, and maintaining robust Python applications.
Hands-on experience in web development with FastAPI, including Pydantic for data validation/schema definition.
Proven skills in asynchronous and parallel programming with practical experience using asyncio.
Experience working in Agile environments and applying core design patterns.
Demonstrated proficiency in .NET Core, ASP.NET Core Web API, and databases (SQL/NoSQL, Entity Framework 6+).
Ability to travel up to 10%, on average, based on client engagements.
Limited immigration sponsorship may be available.
Licensed CPA in state of practice/primary office if eligible to sit for the CPA exam.
Licensed Attorney or Enrolled Agent.
AWS Certified Solutions Architect and/or additional certifications (CRISC, CISSP, SAFe family, CSD, CSSLP) as applicable.
Microsoft Azure proficiency.
Compensation: USD 128,025 - 261,625 per year.

Technologies

Python
FastAPI
Pydantic
asyncio
.NET Core
ASP.NET Core Web API
SQL
NoSQL
Entity Framework 6+
AWS
Microsoft Azure
Angular
MongoDB
NPM
Azure DevOps Build/Release
LangGraph

Benefits

Discretionary annual incentive program

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4d ago

Manager, Data Scientist - Model Risk Office

Capital One Richmond, VA

Richmond, VA

4d ago

$179k - $205k/yr Full time Manager Ai Ml Data Governance

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Job Description

Capital One seeks a Manager, Data Scientist for the Model Risk Office to identify model risks, build and validate ML models, and communicate risk findings to executives.

Location: Richmond, VA (onsite) • Salary: USD 179,400 - 204,700 per year

Responsibilities

Partner with a cross functional team of data scientists, software engineers, and product managers to identify and quantify model risks.
Leverage a broad technology stack—from foundational frameworks such as PyTorch and Hugging Face to orchestration tools like LangChain and vector databases, plus LLMOps and observability platforms—to uncover insights hidden in large, multi modal data.
Develop machine learning models to challenge production champion models and contribute to the governance framework for the next generation of models.
Validate a wide variety of models across multiple business domains within Enterprise Services and present how identified model risks could impact the business to executives.

Technologies

PyTorch
Hugging Face
LangChain
Vector Databases
LLMOps
Python
Scala
R
AWS

BASIC QUALIFICATIONS

Currently pursuing or have obtained a Bachelor's degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) with at least 6 years of data analytics experience
Or a Master's degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) or MBA with quantitative concentration plus at least 4 years of data analytics experience
Or a PhD in a quantitative field plus at least 1 year of data analytics experience
At least 1 year of experience using open source programming languages for large scale data analysis
At least 1 year of experience working with machine learning
At least 1 year of experience utilizing relational or vector databases

PREFERRED QUALIFICATIONS

PhD in a STEM field plus 3 years of data analytics experience
At least 1 year of experience working with AWS
At least 4 years of experience in Python, Scala, or R for large scale data analysis
At least 4 years of experience with machine learning, including GenAI
At least 4 years of experience building or validating models related to fraud detection, digital marketing, cybersecurity, or sensitive data detection

THE IDEAL CANDIDATE IS

Innovative and keeps current with state of the art methods, technologies, and applications
Creative and capable of defining and solving large, undefined problems
Technical and proficient with open source tools and cloud platforms
Statistically minded with modeling, validation, and backtesting experience, including interpretation of confusion matrices and ROC curves, plus experience with clustering, classification, time series, and deep learning
Data guru comfortable handling big data and integrating diverse data sources

TEAM DESCRIPTION

The Capital One Model Risk Office safeguards the company from model failures while enhancing decision making through models, including GenAI related risks. The team blends statistics, software engineering, and business acumen to support Risk Management and the broader Enterprise, with ongoing investments in future capabilities and skills.