Data Scientist working at HP analyzing complex data sets using statistical techniques. Developing data - driven models and insights to improve organizational performance while mentoring project teams.
SF
Hybrid Director, Data Science
Posted last week
About the role
- Principal Data Scientist at Fidelity driving AI/ML innovations and solutions for financial growth. Collaborating cross-functionally to design and deploy advanced analytics and AI technology.
Responsibilities
- Design and deploy state-of-the-art AI and ML solutions to accelerate FI business growth with production reliability and scalability as primary considerations
- Develop and optimize Large Language Model (LLM) applications for business use cases that integrate seamlessly into existing systems
- Implement context engineering strategies and prompt optimization techniques
- Build and maintain Retrieval-Augmented Generation (RAG) systems for semantic search and knowledge retrieval
- Research and prototype emerging AI techniques, always evaluating for production viability and system-wide impact
- Analyze and anticipate how AI implementations affect upstream and downstream systems, data flows, and user experiences
- Design solutions considering scalability, maintainability, observability, and failure modes from the outset
- Collaborate with platform, infrastructure, and application teams to ensure seamless integration
- Document system dependencies, data lineage, and architectural decisions for long-term maintainability
- Collaborate closely with business stakeholders to deeply understand challenges and translate them into technical solutions
- Define and monitor AI performance metrics aligned with business KPIs
- Balance innovation with pragmatism—prioritizing solutions that deliver measurable business value
- Design and implement robust ETL pipelines for both structured and unstructured data
- Build scalable data infrastructure supporting real-time and batch processing needs
- Perform exploratory data analysis to uncover insights and improvement opportunities
- Ensure data quality, governance, and security best practices
- Deploy and manage AI/ML models in cloud environments (AWS) with production SLAs in mind
- Establish monitoring systems for model performance, drift detection, and system health
- Optimize model serving infrastructure for latency, throughput, and cost
- Implement MLOps best practices for continuous integration and deployment
- Build with observability, debugging, and incident response capabilities from the start
Requirements
- Minimum Master’s Degree in Engineering, Computer Science, Mathematics, Computational Statistics, Operations Research, Machine Learning or related technical fields
- 8+ years of AI development experience with proven AI/ML project delivery in production environments
- Demonstrated ability to manage multiple concurrent projects in fast-paced environments
- Ability to pick up new knowledge fast and passionate about continuous learning
- Deep Technical Skills: LLM & Modern AI: Hands-on experience with Large Language Models, prompt engineering, context optimization, and fine-tuning techniques
- AI/ML Engineering: Expert knowledge of statistical models, predictive modeling, time series analysis (regression, classification, clustering, dimension reduction)
- Agentic AI frameworks (multi‑agent orchestration, tool‑use planning, evaluator agents, workflow agents)
- Model alignment, guardrails, safety tuning, hallucination mitigation
- Programming: Advanced proficiency in Python with object-oriented and functional programming paradigms
- Broad Cross-Functional Skills: Business Acumen: Ability to understand financial services domain and translate business needs into technical solutions
- Data Engineering: Production experience with ETL pipeline tools (Airflow, dbt) and big data technologies (Snowflake)
- Deployment & MLOps: Experience deploying and managing applications in cloud environments (AWS preferred)
Benefits
- comprehensive health care coverage and emotional well-being support
- market-leading retirement
- generous paid time off and parental leave
- charitable giving employee match program
- educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career
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