Data Scientist

• Lead client engagements at the intersection of data science, AI, and strategy
• Own projects from scoping through delivery
• Collaborate with clients and cross-functional teams to solve complex marketing challenges
• Apply advanced analytics, modeling, statistics, measurement, and experimentation techniques
• Manage, mentor, and grow analysts and data scientists
• Advise quantitative survey researchers
• Foster innovation, collaboration, and continuous learning
• Ensure delivery of high-quality work
• Pitch new projects and grow client relationships
• Track marketing analytics trends and introduce new methodologies, tools, and techniques
• Advise clients and team members on experimentation, machine learning, and advanced data science methods

Director of Data Science leading AI-driven marketing analytics at Known, a data science and creative agency

Director, Data Science

Director of Data Science leading AI-driven marketing analytics and client engagements at Known, a data science and creative agency. Managing data science teams and driving strategic growth.

• Design and execute rigorous experimental frameworks
• Lead the transition from manual analysis to automated, scalable solutions integrated with the Netflix Experimentation Platform
• Define best practices for trustworthy decision-making at scale
• Advance and implement biddable media models and dynamically priced auctions
• Develop strategies to optimize marketplace mechanics while balancing supply, demand, and member experience
• Partner with Product and Engineering to solve cold-start measurement challenges
• Scale the ad platform across diverse international markets
• Act as a high-level consultant to Product, Strategy, and Engineering teams
• Identify research opportunities, quantify potential business impact, and advocate for resource allocation
• Cultivate partnerships with product, engineering, operations, design, and consumer research stakeholders
• Deliver end-to-end solutions using causal inference, machine learning, and data exploration
• Maintain high standards for documentation and reproducibility

Data Scientist architecting ad experimentation and auction models for Netflix’s global streaming marketplace

Data Scientist 5 – Ads Experimentation

Data Scientist architecting experimentation, causal inference, and auction models for Netflix’s global advertising marketplace. Scaling measurement and marketplace mechanics across international markets.

• Analyze entities across the Plaid network to understand behavior and identify opportunities, anomalies, and risks
• Create foundational metrics, dashboards, and monitoring systems for network health and machine learning model performance
• Evaluate the value and performance of machine learning models using customer and internal data
• Identify opportunities to improve existing models and translate findings into actionable narratives for product and engineering leaders
• Design experiments, define success metrics and guardrails, analyze results, and communicate recommendations to stakeholders
• Analyze Plaid product and customer data to identify opportunities for product improvement and expansion
• Partner with cross-functional teams to build reliable data models and analytics workflows
• Establish the analytics and metrics backbone for the Embedded Insights team
• Support machine learning model development and contribute to Plaid network health and product quality

Senior Data Scientist improving machine learning and financial connectivity products at Plaid

Senior Data Scientist – Embedded Insights

Senior Data Scientist establishing analytics and metrics for Plaid’s financial connectivity network. Evaluating machine learning models and guiding product improvements through experimentation.

• Design, implement, evaluate, and help deploy machine learning models for bidding, pacing, KPI prediction, and forecasting
• Analyze large-scale behavioral and performance data using Spark, Scala/PySpark, SQL, and Python
• Navigate and improve complex legacy codebases
• Collaborate with product managers, engineers, and other data scientists to define problems and deliver end-to-end solutions
• Write clear, concise technical documentation
• Communicate insights effectively to technical and non-technical stakeholders
• Work on optimization and bidding logic for the Nexxen Demand-Side Platform
• Improve bidding, impression-winning, and optimization performance across real-time programmatic advertising exchanges

Data Scientist optimizing Nexxen’s real-time programmatic advertising bidding platform

Data Scientist optimizing machine learning models for Nexxen’s real-time programmatic advertising DSP. Analyzing large-scale data and improving bidding, pacing, and KPI prediction.

• Lead the Sales Analytics team and set its vision across customer acquisition and product expansion sales teams
• Conduct deep-dive analyses to identify revenue drivers and anomalies
• Translate complex data into actionable insights and recommendations for senior leadership and cross-functional partners
• Rebuild foundational data systems with Data Engineering and Service Platform partners
• Align with the Chief Revenue Officer, Sales Operations, Data Engineering, and Service Platform teams on a shared data and infrastructure roadmap
• Evolve sales forecasting methodology using rigorous analytics such as propensity scoring and improved seasonality controls
• Create AI-enabled self-service analytics capabilities for operations partners
• Recruit, mentor, and develop a high-performing analytics team
• Shift the team from reactive query fulfillment toward strategic analysis
• Connect Data Engineering, Analytics Engineering, Data Science, and AI/ML Engineering solutions to revenue-driving analytics

Head of Sales Data Science & Analytics rebuilding Gusto’s revenue data foundation

Head of Sales Data Science, Analytics

Head of Sales Data Science & Analytics leading Gusto’s sales analytics team. Rebuilding revenue data infrastructure and advancing forecasting, causal analysis, and AI-enabled self-service.

• Analyze marketing and business performance
• Build models to understand the impact of marketing investments and strategy
• Identify and communicate insights and opportunities to executives and internal teams
• Perform ad-hoc analyses evaluating marketing spend efficiency
• Build reporting infrastructure and make budgeting recommendations to optimize growth
• Integrate event data with surveys, ad publishers, app store data, and other customer data sources
• Support reporting and business intelligence needs of the Marketing team
• Partner with Marketing teams across business units on marketing measurement, A/B test design and analysis, and data-driven insights

Data Scientist optimizing marketing analytics for Match Group’s global dating platforms

Data Scientist, Marketing Analytics

Data Scientist optimizing marketing measurement, experiments, and reporting for Match Group’s global dating platforms. Delivering actionable growth insights across Tinder, Hinge, and other brands.

• Analyze complex marketing and consumer behavior problems using internal CRM, web and sales data and external market and advertising-platform data
• Build, evaluate and deploy predictive models for attribution, customer lifetime value, churn forecasting and trend analysis using Python and GCP Vertex AI
• Construct optimized BigQuery queries and manage complex datasets
• Cleanse, integrate and automate pipelines for disparate marketing data streams
• Build self-serve analytics dashboards in Tableau for cross-functional marketing teams
• Guide marketing strategy and adoption of Gemini and generative AI
• Use Google Workspace Studio and NotebookLM to compile, synthesize and centralize marketing intelligence and research
• Design and configure customized Gems, AI solutions and AI agents for copywriting, campaign analysis, translation and marketing operations
• Automate workflows across Sheets, Gmail, Docs and Calendar using Google Apps Script
• Gather, clean, transform and preprocess structured and unstructured datasets
• Handle missing data, anomalies and feature engineering
• Analyze sales, marketing and operations data
• Forecast trends and outcomes and recommend actions based on model outputs
• Identify trends, patterns and anomalies and explain performance changes
• Use Python, R, SQL, TensorFlow, Scikit-learn, Spark and Hadoop as needed
• Present findings through visualizations, dashboards and recurring reports using Power BI, Tableau and Looker
• Conduct A/B tests and design experiments to validate hypotheses
• Ensure data consistency and reliability and validate reports and metrics
• Work across Canon business units and departments to develop business insights and predictive results for executive decisions

Data Scientist using AI and predictive analytics to improve Canon’s digital imaging business

Data Scientist applying machine learning, marketing analytics and generative AI at Canon, a global digital imaging company. Building predictive models, dashboards and workflow automations for executive decisions.

• Partner with product, engineering, and user research to build the technology powering Discovery Mode
• Work with data scientists, researchers, product owners, engineers, designers, marketers, and others to develop promotion tools for artists
• Identify impactful product-development opportunities based on user needs
• Define metrics and build dashboards measuring product health and success
• Build and test hypotheses with data scientists to generate actionable product insights
• Improve and expand Spotify’s promotion products
• Contribute to the data science community by evolving best practices and learning new skills
• Maintain rigorous, data-informed decision-making to drive business impact
• Focus on customer engagement and reporting for Spotify’s self-serve Discovery Mode product

Data Scientist improving Spotify’s artist promotion tools and Discovery Mode analytics

Data Scientist – Music Promotion

Data Scientist improving Spotify’s Discovery Mode and promotion tools for artists. Building product analytics, dashboards, and experiments that drive customer engagement and music-industry growth.

• Own model selection and evaluation frameworks for AI-based workflows
• Design cohort and customer/HCP segmentation methodology using real world data sources
• Direct analytical logic and decisioning behind agentic workflows
• Partner with the AI/ML Engineer to translate methodology into production-grade agents and pipelines
• Support strategic and tactical planning for medical and analytical priorities
• Collaborate with the Data Architect/Data Analyst to align analytical outputs with data model and quality standards
• Communicate generated insights and analytical trade-offs to business and technical stakeholders
• Identify new data inputs, analytical techniques, and evaluation approaches to improve workflow quality and adoption
• Mentor and coach junior data scientists and data engineering colleagues
• Lead teams and engage diverse stakeholders

Senior Data Scientist leading AI workflows and healthcare analytics at Pfizer

Senior Data Scientist, AI Lead

Senior Data Scientist leading AI workflow methodology, segmentation, and agent evaluation at Pfizer. Guiding healthcare analytics, production pipelines, and cross-functional teams.

• Lead selection, design, and evaluation of analytical and machine-learning approaches for IDA initiatives and AI-enabled workflows
• Design cohort, customer, and healthcare professional segmentation methodologies using healthcare and real-world data
• Define analytical logic, performance measures, validation methods, and decision criteria for models and agentic workflows
• Conduct advanced analyses to identify patterns, trends, opportunities, and risks informing Medical Affairs decisions
• Document analytical methods, assumptions, limitations, and outputs to ensure reproducibility and fitness for purpose
• Evaluate emerging data-science, artificial-intelligence, and large-language-model techniques
• Prepare, integrate, explore, and analyze complex structured and unstructured datasets
• Develop, test, validate, and refine statistical, machine-learning, natural-language-processing, and AI-based models
• Partner with AI/ML and data engineers to translate methods into production-ready pipelines and workflows
• Collaborate with architecture and governance partners on data models, quality, privacy, and governance
• Establish monitoring for model performance, data drift, output quality, bias, and continued fitness for use
• Provide analytical input to strategy, use-case prioritization, roadmaps, and delivery decisions
• Translate Medical Affairs and business needs into analytical questions, requirements, hypotheses, and evaluation plans
• Communicate findings, recommendations, uncertainty, and trade-offs to technical and nontechnical stakeholders
• Lead projects or analytical workstreams through influence and stakeholder engagement
• Provide technical guidance, mentorship, and coaching to data scientists and analytical colleagues
• Promote data-science standards, reusable methods, peer review, documentation, and knowledge sharing
• Support responsible, transparent, and accountable use of data and AI

Senior Manager applying healthcare data science and AI to Pfizer Medical Affairs

Senior Data Scientist

Senior Manager applying advanced data science and AI to Pfizer Medical Affairs. Leading analytical methods, models, and cross-functional data solutions.

• Own the analytical and technical execution of the Member Onboarding and Customer Experience improvement portfolios
• Design, build, and measure onboarding and customer experience solutions
• Partner closely with the Squad Lead and cross-functional stakeholders
• Apply advanced analytics, experimentation, causal inference, and AI/ML, including LLMs
• Improve member engagement, satisfaction, digital adoption, service utilization, and retention
• Reduce customer experience friction and strengthen ongoing member relationships
• Provide technical leadership and mentor other data scientists
• Surface solution options and trade-offs while ensuring analytical rigor

Senior Data Scientist leading onboarding and customer-experience analytics for CVS Health

Senior Data Scientist leading member onboarding and customer-experience analytics for CVS Health. Applying advanced modeling, experimentation, causal inference, and AI/ML to improve retention.

• Build and tune ML models for fraud and abuse detection using statistical and classical ML techniques
• Develop evaluation frameworks, datasets, and metrics to measure model and mitigation effectiveness
• Analyze false positives/negatives, model drift, and emerging fraud patterns
• Define ground truth, labeling approaches, and fraud taxonomies
• Design experiments and evaluate tradeoffs across precision, recall, customer impact, and fraud loss
• Build dashboards and metrics connecting detection performance to measurable business impact
• Pressure-test models and data for leakage, bias, data-quality issues, and misleading results
• Partner with engineering, product, policy, and risk teams to improve detection and support business decisions

Senior Data Scientist building fraud-detection ML models and measuring effectiveness for Adobe’s creative technology platforms

Senior Data Scientist, ML – Fraud Detection, Effectiveness

Senior Data Scientist building fraud and abuse detection models for Adobe’s creative technology platforms. Measuring model effectiveness through experimentation, analytics, monitoring, and business-impact metrics.

• Own model selection and evaluation frameworks for AI-based workflows
• Design cohort and customer/HCP segmentation methodology using real world data sources
• Direct analytical logic and decisioning behind agentic workflows
• Partner with the AI/ML Engineer to translate methodology into production-grade agents and pipelines
• Support strategic and tactical planning regarding medical/analytical priorities
• Collaborate with the Data Architect/Data Analyst to align analytical outputs with data model and quality standards
• Communicate generated insights and analytical trade-offs to business and technical stakeholders
• Identify new data inputs, analytical techniques, and evaluation approaches to improve workflow quality and adoption
• Mentor and coach junior data scientists and data engineering colleagues
• Lead teams and engage diverse stakeholders to drive transformational change

Senior Data Scientist leading AI analytics workflows for Pfizer’s pharmaceutical business

Senior Data Scientist leading AI workflow methodology, evaluation, and segmentation science for Pfizer’s pharmaceutical business. Partnering with engineering and governance across global sites.

• Own and improve Imprint's onboarding fraud decisioning across the full application journey
• Develop identity verification, KYC controls, application fraud models, policy rules, decline and verification waterfalls, and manual-review strategies
• Build, validate, deploy, and monitor models detecting identity theft, synthetic identity, first-party fraud, and coordinated application abuse
• Evaluate third-party fraud and identity vendors using lift, overlap, coverage, stability, latency, and cost metrics
• Design and analyze A/B tests, shadow tests, holdouts, and champion/challenger strategies
• Balance fraud losses and capture against approval rate, false positives, verification friction, and manual-review volume
• Investigate emerging fraud patterns and decision misses using application, post-booking, and Fraud Operations data
• Build monitoring and AI-powered workflows to detect model drift, population shifts, vendor degradation, data-quality issues, and new attack patterns
• Partner with Fraud Operations, Product, Engineering, Compliance, and Credit Strategy to productionize changes
• Validate impact and communicate recommendations to senior leadership and external partners
• Help protect credit card programs while delivering fast, seamless member experiences

Data Scientist building onboarding fraud models for Imprint's modern credit-card platform

Data Scientist, Fraud Risk

Data Scientist building fraud and identity decisioning for Imprint's modern credit-card programs. Developing models, experiments, and monitoring systems to reduce application abuse and friction.

• Partner with cross-functional data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products
• Leverage PyTorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and related technologies for large-scale numeric and textual data
• Apply Natural Language Processing expertise to Large Language Models, adapting and fine-tuning them for customer-facing applications
• Build machine learning and NLP models through design, training, evaluation, and validation
• Partner with engineering teams to operationalize models in scalable and resilient production systems serving 80+ million customers
• Translate complex technical work into tangible business goals
• Research and evaluate emerging technologies and apply state-of-the-art methods
• Lead stakeholders and support talent development

Senior Manager leading AI and NLP model development for Capital One’s digital banking products

Senior Manager, Data Science – AI Foundations

Senior Manager leading scalable AI, NLP, and LLM development for Capital One’s digital banking products. Building production models that personalize customer financial experiences.

• Partner with data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products
• Build and ship scalable architecture and AI/ML solutions for Capital One’s mobile app
• Develop app features with dynamic and personalized customer experiences
• Enable customers to interact with digital assistant Eno and search useful content
• Leverage PyTorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and other technologies to analyze numeric and textual data
• Apply NLP and LLM expertise to adapt and fine-tune models for customer-facing applications
• Build machine learning and NLP models through design, training, evaluation, and validation
• Partner with engineering teams to operationalize models in scalable, resilient production systems serving 80+ million customers
• Translate complex technical work into tangible business goals
• Research and evaluate emerging technologies and apply state-of-the-art methods
• Lead talent development for the team and beyond
• Influence cross-functional stakeholders and communicate findings to non-technical audiences

Data science manager building scalable LLM and NLP products for Capital One’s mobile app

Manager, Data Science – AI Foundations

Data science manager building scalable LLM and NLP products for Capital One’s mobile app. Leading AI-powered customer experiences across Capital One’s massive data platform.

• Own Partner AI Development & Delivery and GenAI Model Governance
• Lead a multi-geography team and engage MD-level stakeholders across Operations, Marketing, Products, Technology, Model Risk, Fair Lending, and Legal
• Deliver outcomes across expense reduction, revenue growth, customer experience improvement, compliance transformation, and enterprise GenAI capability buildout
• Partner with business units and Technology to deliver GenAI-powered automation across front, mid, and back office banking operations, including call center IVR, Agent Assist, and Collections
• Support enterprise-wide foundational GenAI capabilities including LLM fine-tuning and semantic layer development
• Own the full AI solution lifecycle from concept to production for Personalized Next Best Action decisioning, Campaign Analytics, and Conversational & Contextual Business Insights
• Conceptualize AI-powered tools that accelerate analytics workflows and drive productivity
• Lead the evolution of AI-enhanced modeling techniques to improve development speed and precision
• Manage a large GenAI model portfolio across tuning, upgrades, and maintenance
• Serve as Model Sponsor Delegate with accountability for model ownership, sign-off, and governance under Model Risk Policy
• Build firm-wide GenAI infrastructure including adversarial testing, regulatory testing, guardrails, near real-time monitoring, and AI governance policy co-development
• Establish frameworks tracking outcomes across business deliverables and team performance
• Recruit top talent and lead a specialized team delivering enterprise-grade AI
• Execute with Central AI and business units to redesign processes and deliver measurable change
• Identify, prioritize, and resource high-impact AI solutions with business stakeholders and analytics leadership
• Ensure control processes across Information Security, Platform Security, and Data Security

Citi AI leader governing GenAI models and delivering banking automation across enterprise operations

Senior Vice President – Data Science and Artificial Intelligence Group Manager

Citi AI leader governing GenAI models and delivering production banking automation. Leading multi-geography teams across model risk, compliance, and enterprise AI capabilities.

• Support analytical aspects of business products and services lifecycles
• Collaborate with customers to resolve complex data and reporting issues
• Gather project and data specifications
• Create data sets, operational reports, analytical deliverables, dashboards, business cases, and cost sheet analyses
• Translate high-level business needs into detailed capability requirements and enhancements
• Analyze data to identify business problems, trends, opportunities, and process improvements
• Create and execute test plans; perform root cause analysis and develop corrective action plans
• Verify delivery of customer needs and ensure quality delivery
• Identify, document, and resolve risks, defects, and issues
• Analyze market trends for competitive insights and business value statements
• Mentor Associate, Intermediate, and Senior Data Analysts
• Lead project teams or serve as a subject matter expert on complex cross-functional projects
• Act as primary customer contact and negotiate project requirements versus resources
• Develop alternative solutions while considering regulatory, customer service, and financial impacts
• Lead requirements testing, defect management, requirement walkthroughs, sprint reviews, project status reporting, and documentation
• Provide thought leadership and strategic direction in Data, Product, and Technology Solutions
• Collaborate with Data Software Engineers, Data Architects, Capability Managers, business areas, customers, partners, vendors, technical staff, and project teams
• Ensure required standards and approvals throughout the project lifecycle

Lead Data Solutions Analyst delivering complex healthcare data and reporting solutions for Highmark Health

Lead Data Solutions Analyst

Lead Data Solutions Analyst delivering complex healthcare data and reporting solutions for Highmark Health. Leading requirements, testing, dashboards, and cross-functional projects.

• Partner with cross-functional data scientists, software engineers, and product managers to deliver customer-focused products
• Leverage Python, Conda, AWS, H2O, Spark, and other technologies to analyze large volumes of numeric and textual data
• Build machine learning models through design, training, evaluation, validation, and implementation
• Translate complex data science work into tangible business goals
• Develop generative AI-based solutions for dialogue, text summarization, reading comprehension, speech recognition, image/document processing, and time-series sequencing
• Deliver internal and customer-facing applications with product, technology, and design teams
• Experiment with emerging generative AI technologies and contribute research to NLP and AI/ML conferences

Data scientist building generative AI systems for Capital One’s credit card business

Principal Associate, Data Scientist – Generative AI Systems

Data scientist building generative AI systems for Capital One’s credit card business. Developing machine learning models and customer-facing applications from massive numeric and textual datasets.

• Design and develop new machine learning and Natural Language Processing (NLP) models
• Design, train, and implement ML and deep learning architectures
• Establish evaluation metrics, analyze performance, brainstorm future steps and expansion, and perform exploratory data analysis and data visualization
• Build multi-feature ML classification models for various clinical programs and clients
• Design and develop NLP models for unstructured medical records to improve in-house algorithms
• Oversee delivery of results with analytic insights, interpretations, and recommendations
• Review analytic deliverables, identify and resolve data issues, and recommend investigations
• Design, develop, evolve, and implement processes and procedures ensuring compliance with governance policies
• Propose state-of-the-art technologies and processes to improve efficiency and enhance the reporting platform
• Work at various and unanticipated worksites throughout the United States

Data Scientist building AI healthcare cloud platforms and machine-learning products at EXLService.com

Data Scientist developing AI healthcare cloud platforms and ML/NLP products at EXLService.com. Converting legacy processes and predictive models into advanced healthcare solutions.

Data Scientist jobs in New York

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Director, Data Science

Data Scientist 5 – Ads Experimentation

Senior Data Scientist – Embedded Insights

Data Scientist

Head of Sales Data Science, Analytics

Data Scientist, Marketing Analytics

Data Scientist

Data Scientist – Music Promotion

Senior Data Scientist, AI Lead

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist, ML – Fraud Detection, Effectiveness

Senior Data Scientist, AI Lead

Data Scientist, Fraud Risk

Senior Manager, Data Science – AI Foundations

Manager, Data Science – AI Foundations

Senior Vice President – Data Science and Artificial Intelligence Group Manager

Lead Data Solutions Analyst

Principal Associate, Data Scientist – Generative AI Systems

Data Scientist