Staff Data Scientist, Experimentation Platform Job at Robinhood (Menlo Park)

Staff Data Scientist - GM Motorsports

The Staff Data Scientist is a senior technical leader responsible for driving th...

Location

United States , Austin, Texas; Concord, North Carolina; Warren, Michigan

Salary:

Not provided

General Motors

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Data Science, Statistics, Electrical/Mechanical Engineering, Applied Mathematics, or a related quantitative field
equivalent experience considered
Typically 7+ years of hands-on experience in data science / machine learning roles, with significant experience leading projects or initiatives
Demonstrated experience in complex, high-stakes domains (e.g., motorsports, automotive, aerospace, manufacturing, or similar)
Expert-level proficiency in Python and core data/ML libraries (e.g., NumPy, pandas, scikit-learn, PyTorch and/or TensorFlow)
Strong foundation in statistical modeling, machine learning, and experimental design
Experience building and deploying production ML systems (CI/CD for ML, model serving, monitoring)
Proficiency with SQL and working with large, complex datasets (telemetry, time series, logs, sensor data, etc.)
Familiarity with cloud platforms and modern data stacks (e.g., Azure, Kubernetes, feature stores, ML pipelines)
Experience with time-series telemetry, simulation data, race strategy, or vehicle performance analysis is strongly preferred

Job Responsibility

Define and evolve the data science roadmap for GM Motorsports in alignment with program and competition priorities
Architect end-to-end ML and analytical solutions (from data ingestion and feature engineering to model deployment and performance monitoring)
Establish and enforce best practices in experimental design, model development, validation, and MLOps within the team
Lead high-visibility projects (e.g., race strategy models, performance prediction, simulation, telemetry analytics, audio/vision-based models) from problem framing through delivery
Translate ambiguous racing and business questions into clear problem statements, analytical plans, and measurable success criteria
Own technical decision-making, including method selection, trade-offs, and risk mitigation
Partner with race engineers, competition leaders, and program managers to identify the most valuable AI/ML opportunities
Build models and tools that directly support race weekend decision-making, vehicle development, and long-term performance analysis
Ensure solutions are usable in real workflows: robust, interpretable where needed, and integrated into existing tools and systems
Provide technical mentorship and code/analysis review for junior and senior data scientists

What we offer

This job may be eligible for relocation benefits

Fulltime

Senior Staff Data Engineer- ML & AI Platform

At Marktplaats, data is at the heart of everything we do, but Intelligence is wh...

Location

Netherlands , Amsterdam

Salary:

Not provided

Adevinta

Expiration Date

Until further notice

Requirements

10+ years of experience with a specific focus on the intersection of Data Engineering, MLOps, and AI Infrastructure
Deep knowledge of Spark internals, structured streaming, and performance tuning for large-scale data processing
Proven experience architecting end-to-end ML platforms for Traditional ML (Classic MLOps) while actively enabling the organization on Generative AI concepts
Strong background in building automated pipelines and ensuring system observability
Practical experience building infrastructure for Large Language Models, including managing the complexity of chaining models and tools
Solid experience serving models at low latency and high concurrency using containerized solutions
Ability to speak the language of AI/ML Engineers and effectively bridge the gap between experimental code and production systems
Expert level Python
Experience with PyTorch, Terraform, Terragrunt, Docker, Kubernetes, GitHub Actions, Datadog
Experience with Databricks AI Stack: MLflow, Mosaic AI, Unity Catalog, Feature Store, Databricks Model Serving, Vector Databases

Job Responsibility

Lead the evolution of our Machine Learning & AI Platform, designing the architecture for AI Agents and establishing patterns for Vector Databases
Act as a first mover: validate new Databricks features and integrate them into the platform
Write the guidelines for GenAI development, helping teams transition from notebook experiments to production-grade LLM applications
Design the Feature Store, manage the Model Registry, and set up the infrastructure for Vector Search and RAG (Retrieval Augmented Generation) workflows
Elevate the technical bar of the team, mentoring Staff and Senior engineers on design patterns, code quality, and architectural decisions
Translate complex requirements from ML Engineers and Data Scientists into robust engineering tickets and infrastructure roadmaps

What we offer

An attractive Base Salary
Participation in our Short Term Incentive plan (annual bonus)
Work From Anywhere: Enjoy up to 20 days a year of working from anywhere
A 24/7 Employee Assistance Program for you and your family

Fulltime

Senior Staff Data Engineer- ML & AI Platform

At Marktplaats, data is at the heart of everything we do, but Intelligence is wh...

Location

Netherlands , Amsterdam

Salary:

Not provided

Adevinta

Expiration Date

Until further notice

Requirements

10+ years of experience with a specific focus on the intersection of Data Engineering, MLOps, and AI Infrastructure
Deep knowledge of Spark internals, structured streaming, and performance tuning for large-scale data processing
Proven experience architecting end-to-end ML platforms for Traditional ML (Classic MLOps) while actively enabling the organization on Generative AI concepts
Strong background in building automated pipelines and ensuring system observability
Practical experience building infrastructure for Large Language Models, including managing the complexity of chaining models and tools
Solid experience serving models at low latency and high concurrency using containerized solutions
Ability to speak the language of AI/ML Engineers and effectively bridge the gap between experimental code and production systems

Job Responsibility

Lead the evolution of our Machine Learning & AI Platform, designing the architecture for AI Agents and establishing patterns for Vector Databases
Act as a first mover, validate new Databricks features and integrate them into the platform
Write the guidelines for GenAI development, helping teams transition from notebook experiments to production-grade LLM applications
Design the Feature Store, manage the Model Registry, and set up the infrastructure for Vector Search and RAG (Retrieval Augmented Generation) workflows
Elevate the technical bar of the team, mentoring Staff and Senior engineers on design patterns, code quality, and architectural decisions
Translate complex requirements from ML Engineers and Data Scientists into robust engineering tickets and infrastructure roadmaps

What we offer

An attractive Base Salary
Participation in our Short Term Incentive plan (annual bonus)
Work From Anywhere: Enjoy up to 20 days a year of working from anywhere
A 24/7 Employee Assistance Program for you and your family
A collaborative environment with an opportunity to explore your potential and grow

Fulltime

Staff Scientist, Eats Growth (Economist)

Uber Eats is on a mission to redefine how people discover and enjoy food — and t...

Location

United States , San Francisco, California; New York, New York

Salary:

216000.00 - 240000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

Ph.D., M.S., or Bachelors degree in Statistics, Economics, Operations Research, or other quantitative fields
Minimum 5 years of industry experience as a Data Scientist or equivalent role (2+ if holding a Ph.D.)
Expertise in experimental design and statistical analysis for A/B testing and causal inference
Proficiency in SQL & Python for exploratory data analysis and modeling
Strong analytical skills, with experience extracting user behavior insights from large datasets
Experience with data visualization and dashboarding tools (e.g., Tableau, Matplotlib)

Job Responsibility

Design, execute, and analyze large-scale experiments within the Uber Eats and Uber Rides apps
Perform analytical deep dives to explore topics including conversion funnels, shopping journeys, personalization & ranking, and user retention
Design frameworks for optimizing tradeoffs across competing business objectives to maximize platform growth
Collaborate with Product, Engineering, Design, and other cross-functional partners to understand user behavior and guide future product strategy
Present findings and recommendations to senior technical and business leaders

What we offer

Eligible to participate in Uber's bonus program
May be offered an equity award
Eligible to participate in a 401(k) plan
Various benefits

Fulltime

Data Scientist

The Data Scientist plays a pivotal role in planning, executing, and delivering m...

Location

United States , Camden

Salary:

Not provided

NTT DATA

Expiration Date

Until further notice

Requirements

Master’s, or PhD in Computer Science, Data Science, Engineering, Statistics, Applied Mathematics, Operations Research, or a related quantitative field
Specialization in ML, AI, cognitive science, or data science is highly preferred
3-5 years of hands-on experience planning and executing end-to-end data science projects with demonstrated impact on clinical or operational outcomes in business environments
Advanced programming proficiency in Python or R with strong expertise in machine learning frameworks (scikit-learn, TensorFlow, PyTorch) and statistical analysis tools
Expertise in machine learning and statistical techniques including supervised/unsupervised learning, deep learning, NLP, computer vision, regression models, ensemble methods, and experimental design (A/B testing)
Strong data engineering capabilities including SQL/NoSQL database programming, distributed computing tools (Hadoop, Spark, Kafka), data pipeline development, and experience with cloud platforms (AWS, Azure, GCP)
Production ML and MLOps experience including model deployment, monitoring, containerization (Docker, Kubernetes), version control, and applying DevOps principles to data science workflows
Data visualization and communication excellence with ability to create compelling dashboards (Tableau, Power BI), translate complex technical findings into actionable insights, and present to diverse audiences from executives to frontline staff
Cross-functional collaboration skills with proven ability to work in agile environments, partner with stakeholders to align technical solutions with business objectives, and mentor junior team members
Healthcare domain knowledge preferred, particularly experience with Epic EHR systems, clinical workflows, and healthcare data standards, along with relevant certifications (Clarity /Caboodle, Google Cloud ML Engineer, AWS ML Specialist)

Job Responsibility

Collect, clean, and analyze datasets from diverse internal and external sources, applying advanced data wrangling techniques
Acquire access to various databases and source systems (SQL, NoSQL, graph databases) and create data pipelines
Apply statistical analysis and visualization techniques to explore and prepare data
Design, develop, and validate machine learning, statistical, and optimization models
Select appropriate algorithms and models for AI/ML and test them for accuracy, robustness, and fairness
Perform feature selection and engineering
Integrate domain knowledge into ML solutions
Conduct controlled experiments (A/B and multivariate testing)
Collaborate with MLOps, data engineers, and IT to evaluate deployment options
Continuously monitor execution and health of production ML models

Fulltime

Senior/Staff Software Engineer - Data Platform

Perplexity is looking for experienced Data Platform Engineers to design, build, ...

Location

United States , San Francisco, Seattle, New York City

Salary:

250000.00 - 385000.00 USD / Year

Perplexity

Expiration Date

Until further notice

Requirements

5+ years (Senior) or 8+ years (Staff) of software engineering experience
Strong experience building production data infrastructure systems
Hands-on experience with batch and/or streaming data processing at scale
Deep familiarity with data orchestration systems (Airflow, Dagster, or similar)
Proficiency in Python and at least one additional backend language (Go, TypeScript, etc.)
Strong systems thinking: you understand tradeoffs across reliability, latency, cost, and complexity
Experience supporting ML/AI workflows, training pipelines, or evaluation systems
Familiarity with data quality, lineage, observability, and governance tooling
Prior ownership of internal platforms used by many teams

Job Responsibility

Design and operate large-scale batch and streaming data pipelines supporting product features, AI training/evaluation, analytics, and experimentation
Build and evolve event-driven and streaming systems (e.g., Kafka/Kinesis/PubSub-style architectures) for real-time ingestion, transformation, and delivery
Own batch processing frameworks for backfills, aggregations, and offline computation
Lead the design and operation of data orchestration systems (e.g., Airflow, Dagster, or equivalent), including scheduling, dependency management, retries, SLAs, and observability
Establish strong guarantees around data correctness, freshness, lineage, and recoverability
Design systems that handle scale, partial failure, and evolving schemas
Build self-serve data platforms that empower engineers, data scientists, and analysts to safely create and operate pipelines
Improve developer experience for data work through better abstractions, tooling, documentation, and paved paths
Set standards for data modeling, testing, validation, and deployment
Drive architectural decisions across data infrastructure for storage, compute, orchestration, and APIs

What we offer

Equity
Health
Dental
Vision
Retirement
Fitness
Commuter and dependent care accounts

Fulltime

Staff Applied Research Scientist - Martech AI

We are seeking a highly experienced and strategic Staff Applied Research Scienti...

Location

United States , New York City; Palo Alto; Chevy Chase; Dallas; Seattle; Chicago; Austin

Salary:

130000.00 - 260000.00 USD / Year

Geico

Expiration Date

Until further notice

Requirements

BS in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field, PhD is preferred
At least 6+ years of professional experience delivering applied AI/ML solutions in production, including leading cross-functional initiatives with enterprise impact
Demonstrated ability to leverage LLMs and agentic AI systems to develop and deploy personalized marketing solutions, including individualized content generation, campaign targeting, and optimization of customer engagement/retention/conversion strategies
Strong proficiency in Python and SQL
deep experience with ML frameworks such as PyTorch, TensorFlow, and Scikit-learn
Demonstrated experience establishing KPI frameworks, experimentation, and causal analysis to quantify model impact and inform prioritization
Excellent stakeholder management skills with a track record of driving alignment and adoption across product, engineering, and business teams
Strong written and verbal communication skills
ability to set the right context and explain complex technical topics to varied audiences, including executives

Job Responsibility

Identify High-Impact Opportunities: Proactively surface and shape high-value AI/ML initiatives by engaging with product, engineering, and operations to align technical roadmaps with strategic business goals
Architecture & Technical Direction: Provide architectural leadership for AI/ML solutions impacting multiple stakeholders. Establish standards for scalability, reliability, observability, compliance, and cost efficiency across online and batch systems
Development & Productionization: Lead end-to-end delivery of AI/ML solutions, including model design, data pipelines, feature stores, evaluation, deployment, A/B testing, and monitoring in real-time and batch environments. Ensure clear plans, milestones, and on-time delivery
ROI Measurement & Experimentation: Establish robust mechanisms to quantify business impact, including KPI definition, experimentation frameworks, and causal inference approaches to guide decision-making and prioritize investments
Innovation & Research Integration: Stay current with cutting-edge research in ML, GenAI, and optimization. Prototype and harden novel techniques that push the boundaries of innovation within GEICO’s insurance ecosystem
Set technical direction for multi-quarter research initiatives
build evaluation frameworks, ensure reproducibility/responsible AI, and drive cross-functional adoption
shepherd patents
Cross-Functional Collaboration: Champion collaboration across Product, Engineering, Data Platform, Governance, Legal, and Operations to ensure responsible, compliant, and effective adoption of AI systems
Mentorship & Capability Building: Mentor junior and senior scientists, elevate technical standards (coding, testing, documentation, reproducibility), and foster a culture of scientific rigor and engineering excellence

What we offer

Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family’s overall well-being
Financial benefits including market-competitive compensation
a 401K savings plan vested from day one that offers a 6% match
performance and recognition-based incentives
and tuition assistance
Access to additional benefits like mental healthcare as well as fertility and adoption assistance
Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year

Fulltime

Staff Software Engineer, AI Agent Platform

The Geico AI Agent Platform team is seeking an exceptional Staff Software Engine...

Location

United States , Chevy Chase; New York City

Salary:

115000.00 - 260000.00 USD / Year

Geico

Expiration Date

Until further notice

Requirements

Bachelor’s degree in computer science, Engineering, Mathematics, or a related field
an advanced degree (master’s or Ph.D.) is highly desirable
6+ years of hands-on experience in designing, implementing, and maintaining multi-tenant AIML systems and platforms in production environments
6+ years of experience working with cloud platforms such as Azure and AWS
Extensive expertise in designing and deploying large-scale data pipelines and real-time inference systems and managing the end-to-end AI Agent and/or AIML system development lifecycles, including configuration, evaluation, monitoring, observability and AuthN/AuthR considerations
6+ years of experience working with common backend systems & tools (e.g, Kubernetes, Temporal, OpenSearch, PostgreSQL, Redis, Neo4J, etc.)
Deep understanding of Docker, container optimization, and multi-stage builds
Experience with Prometheus, Grafana, Open Telemetry and distributed tracing
3+ years of experience building front-end web applications using frameworks such as React and/or Next.JS
Deep proficiency in programming languages such as Python, Java, Go, etc., with a strong emphasis on coding excellence

Job Responsibility

Architect and implement scalable multi-tenant backend systems for building AI agent workflows, including agent configuration, offline evaluation, synthetic data generation, workflow simulation, agent marketplace, etc. using Azure Kubernetes Service (AKS), FastAPI, etc., ensuring economy of scale and control cost of maintenance
Collaborate with Design team to architect and implement frontend experiences and workflows for onboarding both technical and non-technical stakeholders, maximizing user adoption and successful AI agent development
Develop observability frameworks to ensure 99.9%+ uptime for AI agent platforms through robust monitoring, alerting, and incident response procedures
Evaluate and (if desirable) integrate cutting-edge GenAI frameworks, libraries and vendors to maintain a state-of-the-art technology stack, including hybrid cloud solutions with AWS/GCP as backup or specialized use cases
Architect and implement scalable, high-performance machine learning platforms and systems capable of processing large data volumes and supporting real-time decision making and workflows
Oversee the end-to-end lifecycle of AI agent applications, ensuring robust testing, deployment, and ongoing monitoring
Ensure adherence to company production readiness standards, security protocols, and regulatory compliance throughout the development lifecycle
Continuously optimize platform performance, reducing latency and improving throughput for AI agent workloads
Design and implement backup, recovery, and business continuity plans for hosted platform applications & services
Design and maintain robust CI/CD pipelines for ML model deployment using Azure DevOps, GitHub Actions, and MLOps tools

What we offer

Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family’s overall well-being
Financial benefits including market-competitive compensation
a 401K savings plan vested from day one that offers a 6% match
performance and recognition-based incentives
and tuition assistance
Access to additional benefits like mental healthcare as well as fertility and adoption assistance
Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year

Fulltime

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Staff Data Scientist, Experimentation Platform

Job Description

Job Responsibility

Requirements

Nice to have

What we offer

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