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13d ago

Senior Data Scientist

Capgemini Brooklyn, NY

Brooklyn, NY

13d ago

$80k - $106k/yr Full time Senior Ai Ml Artificial Intelligence

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Job Description

This role is for a Senior Data Scientist who will develop and deploy AI-driven solutions across predictive modeling, personalization, recommender systems, optimization, and GenAI, with an emphasis on responsible AI. You will partner with business stakeholders and apply advanced AI/ML tools and platforms to support customer engagement and decision optimization use cases.

Role Responsibilities

Develop and deploy AI-driven solutions for customer engagement, personalization, recommendation, decision optimization, and customer insights.
Partner closely with business stakeholders and use advanced AI/ML tools and platforms to address diverse business problems.

Required Qualifications

Master’s or Ph.D. degree in Computer Science, Data Science, Operations Research, Statistics, Applied Mathematics, or a related discipline.
5+ years of prior work experience in Artificial Intelligence, Machine Learning, Data Science, Advanced Analytics, or related technical fields.
Experience with unsupervised and supervised machine learning, predictive modeling, propensity models, recommender systems, deep learning, and graph-based learning techniques.
Experience using advanced NLP frameworks (Transformers, etc.), GenAI solutions, and LLMs.
Experience formulating and solving optimization problems.
Knowledge of model evaluation, tuning, performance measurement, deployment practices, and solution scalability.
Strong verbal, written, and presentation skills, with the ability to communicate effectively with both business and technical teams.
Hands-on experience building predictive machine learning models, recommender systems, ranking models, and prescriptive optimization models.
Proficiency in Python, SQL, MLOps, and modern AI/ML development frameworks such as Scikit-learn, TensorFlow, PyTorch, Hugging Face, and AWS Sagemaker.
Expertise across the AI/ML lifecycle, including experimentation, A/B testing, feature engineering, model development, deployment, monitoring, measurement, and governance.
Experience evaluating, deploying, and governing GenAI solutions, including RAG, knowledge retrieval, agentic AI workflows, LLM fine-tuning, and LLM evaluation frameworks.

Technologies

Python, SQL, MLOps
Scikit-learn, TensorFlow, PyTorch
Hugging Face, Transformers
AWS Sagemaker
LLMs, GenAI, RAG, LLM fine-tuning
A/B testing, graph-based learning techniques

Compensation and Location

Location: Brooklyn, NY (hybrid)
Salary: USD 80,420 - 106,050 per year

Benefits

Flexible work
Healthcare including dental, vision, mental health, and well-being programs
Financial well-being programs such as 401(k) and Employee Share Ownership Plan
Paid time off and paid holidays
Paid parental leave
Family building benefits including adoption assistance, surrogacy, and cryopreservation
Social well-being benefits such as subsidized back-up child/elder care and tutoring
Mentoring, coaching, and learning programs
Employee Resource Groups
Disaster Relief
Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days depending on grade, Company paid holidays, Personal Days, Sick Leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
Life and disability insurance
Employee assistance programs

Nice to Have Skills

Experience applying ML, DL, Econometric, and Foundation Models for time series forecasting
Experience with knowledge graphs and graph-based learning approaches
Experience with constraint or mathematical programming, optimization packages, and solvers such as IBM ILOG CPLEX, Gurobi, or Google OR-Tools

Life at Capgemini

Capgemini supports all aspects of your well-being throughout the changing stages of your life and career.

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13d ago

Lead Data Scientist

Capgemini Brooklyn, NY

Brooklyn, NY

13d ago

$111k - $145k/yr Full time Ai Ml Artificial Intelligence AWS

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Job Description

Lead Data Scientist role at Capgemini, focused on delivering AI and predictive solutions across customer engagement, decision optimization, and responsible GenAI use cases.

Responsibilities

Develop and deploy AI-driven solutions across customer engagement, personalization, recommendation, decision optimization, and customer insights.
Partner with business stakeholders to apply advanced AI/ML tools and platforms to solve business problems.
Build end-to-end solution capabilities spanning model development, deployment, evaluation, and scalability across AI use cases.
Design and operationalize responsible AI systems as part of AI solution delivery.
Drive AI/ML initiatives across multiple customer engagement and decision optimization scenarios.

Requirements

Master’s or Ph.D. degree in Computer Science, Data Science, Operations Research, Statistics, Applied Mathematics, or a related discipline.
10+ years of prior work experience in Artificial Intelligence, Machine Learning, Data Science, Advanced Analytics, or related technical fields.
Experience with unsupervised and supervised machine learning, including predictive modeling and propensity models.
Hands-on experience with recommender systems, deep learning, and graph-based learning techniques.
Experience working with advanced NLP frameworks (Transformers, etc.), GenAI solutions, and LLMs.
Experience formulating and solving optimization problems.
Knowledge of model evaluation, tuning, performance measurement, deployment practices, and solution scalability.
Strong verbal and written communication skills, including presenting findings to both business and technical teams.
Strong hands-on capability building predictive machine learning models, recommender systems, ranking models, and prescriptive optimization models.
Proficiency in Python, SQL, MLOps, and modern AI/ML frameworks including scikit-learn, TensorFlow, PyTorch, and Hugging Face.
Experience using AWS SageMaker and similar platforms for AI/ML delivery.
Expertise across the AI/ML lifecycle: experimentation, A/B testing, feature engineering, model development, deployment, monitoring, measurement, and governance.
Experience evaluating, deploying, and governing GenAI solutions, including RAG, knowledge retrieval, agentic AI workflows, LLM fine-tuning, and LLM evaluation frameworks.

Technologies

Python, SQL, MLOps
Scikit-learn, TensorFlow, PyTorch, Hugging Face, AWS SageMaker
Transformers, LLMs, RAG
GenAI, A/B testing
Graph-based learning techniques, recommender systems
Deep learning, propensity models, feature engineering

Nice to Have

Experience applying ML, DL, Econometric and Foundation Models for time series forecasting.
Experience working with knowledge graphs and graph-based learning approaches.
Experience with constraint and mathematical programming, optimization packages, and solvers (IBM ILOG CPLEX, Gurobi, Google OR-Tools, etc.).

Benefits

Flexible work
Healthcare including dental, vision, mental health, and well-being programs
Financial well-being programs such as 401(k) and Employee Share Ownership Plan
Paid time off and paid holidays
Paid parental leave
Family building benefits including adoption assistance, surrogacy, and cryopreservation
Social well-being benefits such as subsidized back-up child/elder care and tutoring
Mentoring, coaching and learning programs
Employee Resource Groups
Disaster Relief
Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days depending on grade; Company paid holidays; Personal Days; Sick Leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
Life and disability insurance
Employee assistance programs

Salary Transparency

Base salary range for the tagged location: $110,841 to $145,000 per year.
This role may be eligible for additional compensation, including variable compensation, bonus, or commission.
Full time regular employees are eligible for paid time off, medical/dental/vision insurance, 401(k), and other benefits to eligible employees.

Location: Brooklyn, NY (hybrid)

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13d ago

Data Scientist

MANTECH Stafford, VA

Stafford, VA

13d ago

Full time Data Analysis Data Analytics Data Processing

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Job Description

MANTECH seeks a mission-focused Data Scientist to support Marine Corps mission engineering and warfighting analysis with onsite work in Stafford, VA.

Responsibilities

Review, assess, and help validate data science methodologies, analytical models, and workflows supporting mission engineering, warfighting analysis, and capability assessments.
Evaluate analytical rigor, data quality, assumptions, metrics, and methodological soundness across data-driven studies, models, and decision-support products.
Use quantitative, statistical, and computational methods to assess trends, risks, performance, interoperability, capability gaps, and mission impacts across Marine Corps, Naval, and joint systems and concepts.
Develop objective, analytically supported findings and recommendations that inform experimentation, capability development, requirements development, and senior leader decisions.
Produce and present technical reports, briefings, visualizations, and other analytic products for government stakeholders, warfighters, engineers, and senior leaders.
Collaborate across cross-functional teams and, when needed, serve as a program or project lead for small analytic teams supporting mission-focused studies.

Requirements

Education: Master’s degree in operations research, data science, statistics, applied mathematics, engineering, computer science, or a related analytical discipline and at least 2 years of experience conducting quantitative analysis, developing or assessing analytical models, or supporting modeling, simulation, and data science efforts.
Alternate: If holding a bachelor’s degree, 4 years of experience are required.
Experience applying structured analytical methods to complex problems with multiple variables, objectives, constraints, and uncertainties.
Experience reviewing or assessing data science methods, analytic workflows, model outputs, or technical approaches for rigor, credibility, and decision-support value.
Proficiency with analytical and technical tools: Python, R, MATLAB, SQL, SAS, SPSS, machine learning frameworks, and data visualization platforms.
Strong written and verbal communication skills, including experience preparing technical reports, analytic briefings, and visualizations for stakeholders and decision-makers.

Preferred Qualifications

PhD in Operations Research, Data Science, Statistics, Applied Mathematics, Engineering, Computer Science, or a related analytical discipline.
Experience supporting Marine Corps, Navy, or joint warfighting analysis, mission engineering, concept development, experimentation, capability assessments, or requirements development.
Familiarity with mission engineering methodology, including mission architecture, mission threads, measures and metrics, and scenario-based analysis.
Experience conducting trade-off studies, sensitivity analysis, optimization, interoperability assessments, operational effectiveness analysis, or mission-level capability evaluations.
Familiarity with simulation modeling environments, data management practices, and traceable analytic products that support decision-making.

Security Clearance

Must possess a current/active TS/SCI security clearance.

Location and Work Environment

Location: Stafford, VA (onsite).
Office work environment with occasional travel to outdoor test and evaluation sites.

Physical Requirements

Remain in a stationary position 50% of the time.
Occasionally move about inside the office to access file cabinets, office machinery, meeting spaces, and collaborative work areas.
Frequently communicates with co-workers, management, and customers, including in meetings and presentations.
Must be able to exchange accurate information during these communications.

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13d ago

Senior Data Scientist

Institute For Medical Research Inc Durham, NC

Durham, NC

13d ago

$83k - $83k/yr Full time Senior Clinical Data Science Data Analysis

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Job Description

The Senior Data Scientist at Institute For Medical Research Inc will help advance clinical research and quality-improvement work for the Durham VA Cardiology program. The position combines clinical informatics, biostatistics, data engineering, and workflow automation to move from study planning and data sourcing through analysis, reporting, and dissemination.

Working onsite in Durham, NC, you will partner with cardiology stakeholders and research teams to translate clinical and research questions into reliable datasets, rigorous statistical analyses, and practical reporting tools that can be sustained across current and future studies.

What you’ll do

Collaborate with clinical investigators to define cohorts, outcomes, exposures, time windows, and data requirements for observational studies, clinical trials, implementation projects, and quality-improvement initiatives.
Extract, integrate, transform, and curate structured clinical data from the VA Corporate Data Warehouse and other approved sources, including laboratory, medication, procedure, diagnosis, encounter, vital-sign, and longitudinal follow-up data.
Build reusable, well-documented data pipelines, analytic datasets, data dictionaries, validation checks, and source-to-output traceability procedures.
Conduct systematic data quality assessment, covering completeness, consistency, duplicate identification, temporal validation, and reconciliation with clinical or operational source systems.
Provide statistical programming and analytic support using methods appropriate to the study design, including descriptive, inferential, regression, longitudinal, survival, and other analyses.
Support study design and feasibility by contributing to analytic plans, variable definitions, sample-size considerations, interpretation of findings, and sensitivity or subgroup analyses.
Create validated tables, listings, figures, visualizations, and summary reports for investigators, sponsors, clinical teams, and leadership.
Help prepare protocols, abstracts, manuscripts, presentations, grant applications, and other scientific deliverables, including analytic documentation and methods sections.
Design and maintain research data-capture, workflow, and reporting solutions using platforms such as REDCap, Power BI, SharePoint, Power Automate, and other approved tools.
Automate processes such as patient identification, eligibility screening, task generation, follow-up scheduling, reminders, notifications, missing-data review, and escalation of overdue activities.
Develop operational and research dashboards to track enrollment, follow-up, data completeness, clinical measures, study milestones, and agreed performance indicators.
Partner with end users to test, document, refine, and sustain reporting tools and automated workflows while reducing unnecessary manual processing.
Evaluate and apply advanced statistical, predictive, or machine-learning methods when appropriate, aligned to the clinical question, data available, study maturity, and validation needs.
Support Cardiology research involving ECG and echocardiographic data, including development and evaluation of prediction models with emphasis on clinical interpretability, reproducibility, and generalizability.
Develop and implement reproducible machine-learning pipelines, covering data preparation, quality control, model development and evaluation, validation, and reporting.
Assess new analytic methods and data sources and recommend practical approaches that complement established clinical informatics and biostatistical workflows.
Serve as a data-science and informatics resource for Cardiology investigators and multidisciplinary teams, communicating technical findings clearly to both technical and nontechnical audiences.
Apply applicable VA privacy, information-security, regulatory, and research-governance requirements across data access, processing, analysis, reporting, and dissemination.
Promote reproducible research through version control, standardized programming practices, transparent documentation, validation, and clear communication of analytic assumptions and limitations.
Provide technical guidance or mentorship to analysts, trainees, investigators, and project staff as needed.

Requirements

Advanced training or equivalent professional experience in data science, biostatistics, biomedical or clinical informatics, epidemiology, engineering, computational biology, or a related quantitative field.
Substantial experience analyzing complex clinical, biomedical, or health-services data and collaborating with clinical or research teams.
Advanced proficiency in SQL and one or more analytic languages such as R, Python, or SAS, with demonstrated ability to develop validated, reproducible workflows.
Experience with statistical analysis, data visualization, research reporting, and interpretation for observational or clinical-study data.
Ability to work independently, manage multiple projects, establish analytic priorities, and communicate effectively with scientific, clinical, operational, and leadership audiences.

Technologies

SQL
R
Python
SAS
REDCap
Power BI
SharePoint
Power Automate
VA Corporate Data Warehouse
VINCI

Preferred qualifications

Experience with cardiovascular research, VA data systems, VA Corporate Data Warehouse/VINCI, or comparable large-scale electronic health record repositories.
Experience developing clinical research databases, dashboards, and workflow automation using REDCap, Power BI, SharePoint, Power Automate, or related platforms.
Experience with longitudinal analysis, survival analysis, predictive modeling, machine learning, or analysis of ECG and other physiologic data.
A record of contributions to peer-reviewed publications, grant proposals, clinical research programs, or implemented analytic products.

Location: Durham, NC (onsite)

Compensation: USD 82,500 per year

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13d ago

Senior Data Scientist

LendingTree Charlotte, NC

Charlotte, NC

13d ago

$130k - $170k/yr Full time Senior Artificial Intelligence Data Analysis

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Job Description

Join a team that builds predictive models and AI/ML solutions to solve real business problems. This Senior Data Scientist role is based in Charlotte, NC (onsite), with attendance at the Southend office three days a week. You will lead complex analysis and model development, work closely with business and technical partners, and help strengthen data science practices through mentorship and continuous improvement.

Compensation: USD 130,000 to 170,000 base pay per year. Annual performance bonus eligibility is included, and base pay may vary based on internal factors, job-related knowledge, skills, and experience.

Responsibilities

Execute data science strategies and roadmaps by translating business objectives into analytical solutions and AI/ML models.
Design, develop, and deploy predictive models, machine learning algorithms, and AI solutions.
Partner with teammates and stakeholders to understand requirements, explore data, and deliver actionable insights.
Validate, test, and calibrate models to ensure validity, reliability, and robustness, then monitor outcomes and refine performance.
Communicate complex technical solutions and findings clearly, connecting analytical results to business needs.
Guide junior team members and improve data science practices through continuous improvement, knowledge sharing, and exploration of new methods.
Develop and implement reliable models tied to clearly defined business needs and measurable, actionable outcomes.
Establish validation and monitoring practices, using model outcomes to guide ongoing improvements.
Build productive partnerships across teams and support business decisions through effective communication of analytical insights.
Support junior teammates while contributing to more consistent, higher-quality data science execution.

Requirements

Bachelor’s or master’s degree in Computer Science, Data Science, Statistics, or a related field.
At least five years of experience in a data science role, with strong SQL and Python skills.
Strong skills in data analysis, profiling, and statistics, including experience with SQL databases and analytical tools such as Oracle, SQL Server, MySQL, Pandas, NumPy, ggplot, Shiny, SciPy, scikit-learn, and Matplotlib.
Proficiency with machine learning and deep learning algorithms, with experience using frameworks such as TensorFlow, PyTorch, Spark ML, Torch, Hugging Face, Keras, Caffe, and CNTK.
Understanding of cloud computing and experience deploying models in AWS, Azure, or GCP.
Familiarity with model development and willingness to explore deployment strategies to bring models into operational use.
Strong analytical and problem-solving skills with attention to detail and the ability to derive actionable insights from complex datasets.
Clear communication skills, including the ability to explain technical concepts to diverse audiences.

Technologies

SQL, Python, Oracle, SQL Server, MySQL, Pandas, NumPy, ggplot, Shiny, SciPy, scikit-learn, Matplotlib
TensorFlow, PyTorch, Spark ML, Torch, Hugging Face, Keras, Caffe, CNTK
AWS, Azure, GCP

Benefits

Medical, dental, and vision insurance
401(k) matching
Generous time off
Wellness programs and resources
Annual performance bonus eligibility

What Will Help You Thrive

A collaborative approach and the ability to build strong relationships across technical and business teams.
Agility and composure when managing multiple projects in a fast-paced environment.
Curiosity about emerging data science methods and a proactive approach to learning and adapting.
An interest in mentoring junior teammates and improving how the team works.
Prior fintech or software engineering experience.
A PhD in Computer Science, Data Science, Statistics, or a related field.

Work authorization: This position is not eligible for immigration sponsorship. Please do not apply if you will need employer sponsorship now or in the future to begin or continue employment.

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13d ago

Load Forecasting Data Scientist

ISO New England, Inc Hartford, CT

Hartford, CT

13d ago

$86k - $146k/yr Full time Analytics Data Analysis Data Analytics

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Job Description

ISO New England, Inc offers a hybrid role in Hartford, CT where you can lead and develop forecasting tools that support electricity demand planning. You will work on next generation analytics and predictive modeling across short- and long-term time horizons, while collaborating with others on modeling, data management, software, and data pipelines. The role includes competitive pay, performance-based compensation, and benefits designed to support your growth and wellbeing.

What you’ll do

Drive analytical, programming, modeling, and data management work independently and as part of a team.
Define and document problem statements, project requirements, and related workflows to support efficient, effective solutions.
Use a curious mindset and hands-on effort to improve existing processes and to create new forecasting methods, tools, and software.
Share technical work clearly with diverse audiences through written reports and presentations.
Focus on quality outcomes by leading development of data pipelines, reusable software packages, and visualizations.
Stay current with forecasting research and industry best practices, evaluating and implementing relevant approaches strategically.

What you bring

Bachelor’s degree in Economics, Mathematics, Engineering, Operations Research, or a related field.
3+ years of experience in the energy industry in forecasting, data analytics, or equivalent.
Proficiency in at least one advanced programming language: Python, R, MATLAB, or SAS.
Hands-on experience developing software in a collaborative team environment.
Experience working with big data, geospatial analytics, and/or probabilistic forecasting.
Experience building applications that ingest and use data from multiple sources and formats, including data wrangling/data munging.
Excellent written and verbal communication skills.

Tools you’ll use

Python
R
MATLAB
SAS

Benefits and work setup

Competitive compensation with a base salary plus a performance bonus (USD 86,000 to 146,000 per year).
Enhanced 401(k) and financial planning support.
Tuition reimbursement and professional development opportunities.
Wellness programs, including an onsite gym.
Flexible work hours.
Employee Business Networks.
Onsite luncheon spaces with free coffee and a variety of dining options.
Hybrid environment with 3 days/week onsite in Hartford, CT.
Distance-based relocation assistance available.

Nice to have (not required)

Experience in electricity consumption modeling or economic modeling in the energy sector.
Knowledge of distributed energy resources (such as photovoltaics and batteries), electric vehicles, and/or cold-climate heat pumps.

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13d ago

Data Scientist

COUNTRY Financial Bloomington, IL

Bloomington, IL

13d ago

$132k - $182k/yr Full time Artificial Intelligence Data Analysis Data Analytics

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Job Description

COUNTRY Financial is hiring a Data Scientist to apply advanced analytics, machine learning, and artificial intelligence in support of measurable business outcomes. This position sits within the enterprise Data & Analytics Solution Delivery team, where scalable solutions and predictive modeling are used to create value from enterprise data.

In this role, you will partner with business stakeholders to clarify problems that can be addressed through analytics, then build and evaluate data-driven solutions. The work includes developing supervised and unsupervised machine learning, forecasting, and optimization approaches, along with the data practices required to manage versioning and documentation.

What you’ll do

Work with business teams to understand the problems that need to be solved
Help translate business needs into analytics-ready problem statements
Perform data mining and transform raw data into actionable business information
Develop and implement analytics solutions using advanced statistical methods and machine learning techniques
Design, develop, and evaluate predictive models and advanced algorithms to maximize value extracted from data
Validate model performance using appropriate standards and error metrics
Manage version control and maintain documentation for data
Develop and produce supervised and unsupervised machine learning, forecasting, and optimization