Senior Data Scientist, Generative AI Products, HBS Foundry

About the Role

Key Responsibilities

• Design, develop, and deploy generative AI models using techniques like natural language processing and machine learning to power interactive tools on HBS Foundry.
• Build data science pipelines from feature generation, data visualization, and models evaluation; design solutions, build code, and provide documentation to maximize reusability and scalability.
• Design and implement efficient data pipelines for data collection, cleaning, labeling, and preprocessing, ensuring dataset quality for large language model training.
• Develop multi-agent AI tools that assess submissions, generate pitch decks, financial projections, marketing strategies, and simulate entrepreneurial interactions.
• Integrate AI tools into the HBS Foundry platform seamlessly for user accessibility and utilization.
• Collaborate on technical vision to accelerate product impact through cutting-edge LLM innovations.
• Build guardrails, compliance rules, and oversight workflows into AI tools and the platform.
• Monitor, debug, track, and resolve production issues, ensuring projects proceed on time and within budget.
• Present prototypes and progress updates to stakeholders.
• Stay up to date on AI/ML research and collaborate with team members to deliver high-quality AI experiences.

Requirements

• Minimum of seven years' post-secondary education or relevant work experience.
• Advanced degree in computer science, data science, engineering, or a related field within AI/ML.
• 3+ years of experience building generative AI models and tools.
• Expertise in NLP, deep learning, and relevant techniques.
• Strong programming skills in Python and frameworks like TensorFlow.
• Experience with workflows such as retrieval augmented generation, model chaining, dynamic prompting, PEFT/SFT using Langchain and similar tools.
• Experience integrating AI into consumer-facing applications, including front-end and back-end development.
• Experience establishing model guardrails and developing bias detection and mitigation techniques.
• Experience with embedding models, tuning vector databases, and improving semantic search performance.
• Experience working with relational SQL and NoSQL databases, big data tools (Hadoop, Spark, Kafka), and cloud providers (preferably AWS).
• Proficiency with version control systems like Git, containerization and orchestration tools such as Docker and Kubernetes, and API development.
• Understanding of software engineering best practices like CI/CD.
• Excellent communication and collaboration skills.

Nice to Have

• Experience working in a startup environment.
• Experience operationalizing end-to-end machine learning applications.
• Experience with bias detection and mitigation tools such as NeMo.
• Proficiency with various prompting techniques and finetuning embedding models.
• Experience with setting up and tuning vector databases for semantic search.

Qualifications

• Advanced degree in computer science, data science, engineering, or a related field within AI/ML.
• Minimum of seven years' post-secondary education or relevant work experience.

Benefits & Perks

• Generous paid time off including parental leave.
• Medical, dental, and vision health insurance coverage starting on day one.
• Retirement plans with university contributions.
• Wellbeing and mental health resources.
• Support for families and caregivers.
• Professional development opportunities including tuition assistance and reimbursement.
• Commuter benefits, discounts, and campus perks.