End-to-end ownership of a strategic customer intelligence platform combining ML, GenAI, and large-scale transaction data to identify customer patterns and support personalization and marketing.
Compensation
Broadband Salary Range: $64,000 – $106,000.
Responsibilities
Lead the technical transition of the third party-developed engine into a fully owned CTC capability.
Master existing code, prompts, models, data pipelines, and architecture.
Run the production platform end-to-end, including scheduled scoring, catalogue refreshes, model and prompt releases, and pipeline monitoring.
Own ML capabilities including transaction classification, clustering, feature development, model validation, and drift management.
Own GenAI capabilities including prompt architecture, context construction, model selection, and prompt tuning.
The role involves developing AI-driven methods, LLM-based conversational interfaces, and retrieval systems to improve the discovery and usability of atmospheric data.
Responsibilities
Research, develop, and deploy AI/ML methods, including LLM-based conversational interfaces and retrieval systems, that improve discovery and usability of ARM data.
Build and maintain training and evaluation datasets derived from ARM metadata records.
Work with data scientists, database engineers, software engineers, and DevOps engineers to take systems from prototype to production.
Support researchers and developers in creating tools for the ARM Data Center.
Grow into a leadership role in AI/ML engineering for the group, demonstrated through deliverables to sponsors, platform development, technical presentations and demonstrations, and, where appropriate, inventions, patents, or copyrights.
A senior individual-contributor role acting as the technical authority guiding advanced AI across the commercial landscape—from traditional ML to Generative and agentic AI.
Responsibilities
Define and drive the technical vision, roadmap and architecture for traditional ML, Generative AI and agentic AI capabilities
Provide hands-on technical leadership to project teams; set design direction, review architectures and code, remove blockers
Lead the design of multi-agent systems and LLM applications, including orchestration, tool use, memory, guardrails and human-in-the-loop patterns
Establish standards for evaluation, including automated and human-in-the-loop methods, benchmarking, and quality gates
Drive approaches to fine-tuning, distillation and reinforcement learning (including RL from feedback)
As a Data Scientist, you will work closely with clients and cross functional teams to define project scope, ensure technical feasibility, and drive delivery excellence.
Responsibilities
Mapping the end-to-end data science approach and designing the associated software architecture for projects
Driving the technical scoping and feasibility assessment of new projects
Building strong client relationships by acting as a technical advisor and shaping the direction of current and future engagements
Delivering bespoke algorithms and scalable software solutions that adhere to best practices for high-stakes decision-making
Setting the technical bar for the project team, ensuring the highest standards of code, rigour, and delivery quality (IC leadership)
Design, develop, and deploy machine learning and artificial intelligence solutions that drive business decision-making and operational excellence.
Responsibilities
Develop, validate, deploy, and monitor machine learning models that support forecasting, optimization, customer intelligence, operational decision-making, and business growth.
Design and implement advanced predictive models using supervised and unsupervised learning techniques.
Perform feature engineering, model selection, hyperparameter tuning, and performance evaluation.
Establish model governance processes, including documentation, explainability, fairness assessments, and monitoring.
Translate business challenges into analytical frameworks and data-driven solutions.
Data Science turns Zoox's driving, fleet and business data into decisions and automation. Interns may work on Autonomy Software V&V or Core/Domain Data Science teams.
Compensation
The monthly salary range for this position is $6,500 to $9,500. Compensation will vary based on geographic location and level of education.
Responsibilities
Use coding and analytical skills to derive insights that inform decisions and automation
Test new frameworks and algorithms to improve model performance
Work on a project such as drift monitoring, automated model retraining, predictive modeling, similarity search or statistical testing
Analyze real-world driving data to identify patterns, measure autonomy performance, and inform stack improvements
Contribute to metrics platforms that track miles-per-disengagement, driving behavior clusters, and safety-critical events
Requirements
B.S., M.S., Ph.D., or advanced degree in data science, statistics, computer science, or a related engineering program
Data Scientist focused on Revenue Management & Network Optimization, building end-to-end machine learning solutions for dynamic pricing, demand forecasting, and revenue optimization.
Responsibilities
Turn business challenges into well-defined analytical problems
Build and deploy end-to-end machine learning solutions
Design, train, and maintain models that power revenue optimization
Deliver dynamic pricing and AI-driven revenue optimization at scale
Build and deploy algorithms for demand forecasting, purchase probability, and revenue optimization
Forward Deployed Engineers build and prototype AI solutions within business unit teams, using AI coding assistants and multi-agent workflows to deliver AI proofs of concept.
Locations (4)
Cambridge, Massachusetts, United States
Waltham, Massachusetts, United States
Rockville, Maryland, United States
San Francisco, California, United States
Compensation
If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA, the annual base salary for new hires in this position ranges $95,700 to $159,500.
Responsibilities
Contribute to BU use case engagements—prototyping, demoing, refining—under senior FDE guidance
Lead Data Scientist leading AI and ML initiatives for fraud detection and risk intelligence within Mastercard’s Security Solutions portfolio.
Responsibilities
Lead and directly contribute to the design, development, deployment, and optimization of machine learning models for fraud detection, risk scoring, anomaly detection, and related security applications.
Define, build, and guide scalable AI and ML pipeline architecture supporting model training, validation, deployment, monitoring, retraining, and continuous improvement.
Hands‑on design and implementation of Generative AI and Agentic AI solutions leveraging LLMs, RAG, reasoning and planning workflows, Chain‑of‑Thought prompting, tool/function calling, and multi‑agent orchestration.
Work with large‑scale transactional datasets using distributed computing technologies such as Spark and Databricks.
Implement MLOps best practices, including CI/CD, model governance, observability, experimentation frameworks, and performance monitoring.
Data Systems AI / ML EngineerNewOak Ridge National Laboratory · Oak Ridge, US
Senior Data ScientistNewFaculty · Sydney, Australia
Data Science Intern [Summer 2027]Zoox · Foster City, US
Lead Data ScientistMastercard · Gurgaon, India