Position Description

Harvard Business School will not offer visa sponsorship for this opportunity.

As a Senior Data Scientist, you will collaborate with the Data Science and Machine Learning team and will create data science, machine learning, and AI solutions to better address the needs of our constituents (students, alumni, faculty, researchers, staff, and community at large). You will have the chance to guide and continuously improve the ways in which we engage, educate, and empower people around the world, combining the best of human touch and technology scale. You will experiment with everything from the latest AI algorithms and techniques to blended and immersive environments, multi-modal and varied-form content, and the most innovative research and teaching methodologies. You will be highly influential in advancing our LLM applications and guide teams towards impactful and ethical AI. We seek an expert who is eager to grow and disseminate GenAI model expertise across the organization.

In this role, you will translate the needs of our cross-functional stakeholders into user-facing applications that leverage NLP techniques and large language models (LLMs). As a Sr. Data Scientist on our GenAI applications team, you will work on products like conversational search interfaces, chatbots, text summarizers, recommender engines, and more based on the needs of the constituents. You will partner with Product Managers, Machine Learning Engineers, Cloud Platform Engineers, and cross-functional partners to develop production-grade algorithms. Your innovations will drive value creation through personalized engagement, expanded reach, and experimental ways of learning that will continue the Harvard Business School leadership in education, business, and societal impact.

• Architect the overall framework and infrastructure for GenAI products like search interfaces, bots, summarizers, etc. Develop and implement techniques to optimize model performance to meet specific product goals.
• Collaborate closely with product management and engineering leads to align on technical roadmap. Guide engineering teams to effectively leverage LLM capabilities in product implementations.
• Establish protocols and systems for building fair, accountable and transparent LLM-based applications. Lead efforts to proactively assess and mitigate risks due to model biases or failures.
• Implement robust feedback pipelines, monitoring and corrections to ensure model safety.
• Design and oversee curation of high-quality datasets tailored for LLM training for each product. Build data science pipelines from feature generation, data visualization and models evaluation; design the solution, build initial code and provide documentation with ways of working to maximize time to value and re-usability.
• Communicate clearly and effectively to technical and non-technical audiences, verbally and visually, to create understanding, engagement, and buy-in. Contribute novel research and analyses to leading academic conferences and journals.
• Identify trends and opportunities to drive innovation, both in what we do and how we do it; evaluate new data science, machine learning, and AI technologies and tools that can boost team performance, innovation and business value. Proactively analyze latest developments in large language models to deeply understand model capabilities, limitations, and best practices. Develop techniques to continually improve language understanding and model training.
• Embody the values and passions that characterize Harvard Business School, with empathy to engage with colleagues from a wide range of backgrounds.
• Mentor and develop junior data scientists in state-of-the-art GenAI methods
• Set technical vision and lead initiatives to accelerate product impact through cutting-edge LLM innovations.
• Complete other responsibilities as assigned.

Basic Qualifications

• Minimum of seven years? post-secondary education or relevant work experience

Additional Qualifications and Skills

Other Required Qualifications:

• Minimum of three years? experience in developing machine learning models with a track record of creating meaningful business impact and working with multiple stakeholders.
• Experience with production RAG pipelines and agentic information retrieval and search systems, with the ability to write production level code.
• Minimum of five years? experience with Python.
• Minimum of three years' experience building production NLP and deep learning models using PyTorch/Tensorflow, along with using large language model architectures (BERT, GPT-3 etc.)
• Experience building advanced workflows such as retrieval augmented generation, model chaining, dynamic prompting, PEFT/SFT, etc. using Langchain and similar tools.
• Experience establishing model guardrails and developing bias detection and mitigation techniques for AI applications.
• Proficiency with various prompting techniques, with a clear understanding of tradeoffs between prompting and finetuning.
• Experience with finetuning embedding models and tuning vector databases to improve performance of semantic search and retrieval systems.
• Deep understanding of underlying fundamentals such as Transformers, Self-Attention mechanisms that form the theoretical foundation of LLMs.
• Experience with cloud computing platforms and tools - AWS
• Experience operationalizing end-to-end machine learning applications.

Additional/Desired Qualifications:

• Advanced degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline desired.

Additional Information

This role has the possibility of being remote or hybrid.
Remote work may be considered for individuals living at least 100-mile radius from campus and where all work will be completed within a state that Harvard is registered to do business in (CA - exempt roles only, CT, GA, IL, MA, MD, ME, NH, NJ, NY, RI, VA, VT or WA).
We consider hybrid to be a combination of remote and 3 days per week onsite work at our Boston, MA based campus.
Specific hours and days onsite will be determined by business needs and are subject to change with appropriate advanced notice.

We may conduct candidate interviews virtually (phone and/or via Zoom) and/or in-person for this role.

Harvard Business School will not offer visa sponsorship for this opportunity.

Culture of Inclusion: The work and well-being of HBS is profoundly strengthened by the diversity of our network and our differences in background, culture, national origin, religion, sexual orientation, and life experiences. Explore more about HBS work culture here https://www.hbs.edu/employment.

Benefits

We invite you to visit Harvard's Total Rewards website (https://hr.harvard.edu/totalrewards) to learn more about our outstanding benefits package, which may include:

• Paid Time Off: 3-4 weeks of accrued vacation time per year (3 weeks for support staff and 4 weeks for administrative/professional staff), 12 accrued sick days per year, 12.5 holidays plus a Winter Recess in December/January, 3 personal days per year (prorated based on date of hire), and up to 12 weeks of paid leave for new parents who are primary care givers.
• Health and Welfare: Comprehensive medical, dental, and vision benefits, disability and life insurance programs, along with voluntary benefits. Most coverage begins as of your start date.
• Work/Life and Wellness: Child and elder/adult care resources including on campus childcare centers, Employee Assistance Program, and wellness programs related to stress management, nutrition, meditation, and more.
• Retirement: University-funded retirement plan with contributions from 5% to 15% of eligible compensation, based on age and earnings with full vesting after 3 years of service.
• Tuition Assistance Program: Competitive program including $40 per class at the Harvard Extension School and reduced tuition through other participating Harvard graduate schools.
• Tuition Reimbursement: Program that provides 75% to 90% reimbursement up to $5,250 per calendar year for eligible courses taken at other accredited institutions.
• Professional Development: Programs and classes at little or no cost, including through the Harvard Center for Workplace Development and LinkedIn Learning.
• Commuting and Transportation: Various commuter options handled through the Parking Office, including discounted parking, half-priced public transportation passes and pre-tax transit passes, biking benefits, and more.
• Harvard Facilities Access, Discounts and Perks: Access to Harvard athletic and fitness facilities, libraries, campus events, credit union, and more, as well as discounts to various types of services (legal, financial, etc.) and cultural and leisure activities throughout metro-Boston.

Work Format

Hybrid (partially on-site, partially remote)


Commitment to Equity, Diversity, Inclusion, and Belonging
Harvard University views equity, diversity, inclusion, and belonging as the pathway to achieving inclusive excellence and fostering a campus culture where everyone can thrive. We strive to create a community that draws upon the widest possible pool of talent to unify excellence and diversity while fully embracing individuals from varied backgrounds, cultures, races, identities, life experiences, perspectives, beliefs, and values.

EEO Statement
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions, or any other characteristic protected by law.

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