ML Scientist

Harvard Business Publishing (HBP) – the leading destination for innovative management thinking. We reach lifelong learners to improve the practice of management in a changing world. This mission inspires each of us to unlock the leader in everyone – including you!

The opportunity:

The ML Scientist at Harvard Business Publishing (HBP) plays a critical role in supporting analytics functions and driving product innovation through the application of machine learning and data science techniques. This position involves working on inferential data science and predictive ML projects, directly participating in product development, and collaborating cross-functionally with technical teams and business subject matter experts to enhance HBP's product offerings. The ideal candidate will have a strong background in experimental design, causal inference, and ML infrastructure as practiced in an applied setting for product development, with a passion for leveraging data to extract valuable insights and improve business outcomes.

What You’ll Do:

• Lead inferential data science and predictive ML projects: Work closely with analytics teams to design and execute experiments, perform causal inference, and derive strategy-influencing insights from data. Translate these findings to cross-functional stakeholders including technical teams like software engineering and business stakeholders like sales, marketing, and editorial
• Derive attributes from core data assets: Extract meaningful attributes about HBP product end users, content, and the marketplace to support insight extraction and enhance product experiences
• Automate routine business reporting: Develop automated solutions for routine business reporting, including leveraging LLMs for data labeling, analysis, and transformation, catering to both internal and external users
• Participate as a technical resource in product development: Contribute as a technical expert in product development, focusing on the analytical data science role supporting innovation with data and AI
• Develop and maintain ML and AI infrastructure: Collaborate with HBP and HBS technical teams to develop and maintain the infrastructure needed for product-facing ML and AI applications
• Contribute to data engineering: Ensure quality and integrity of user, content, and market data by collaborating with the Data Engineering team to build and maintain data pipelines and product-facing APIs for HBP's central data warehouse relevant to products the AID is supporting

What you'll bring:

• Experience: 5+ years in data science, ML/AI development, or a closely related field, with a proven track record of delivering business-influencing insights
• Collaboration: Excellent communication and stakeholder management skills, with the ability to work effectively across multiple teams and departments
• Innovation: A strong passion for innovation and the ability to think creatively about how AI and ML can be applied to solve business problems and enhance product offerings
• Data science: Extensive experience answering questions with and deriving strategic insights from data, including proficiency in probability and statistics, data querying and transformation with SQL, and developing interactive data dashboards and applications with tools like Streamlit
• Programming Skills: Excellence in Python programming and experience with relevant data science and AI/ML packages such as pandas, scikitlearn, pytorch, and Langchain. Extensive experience in collaborative development with git

Preferred/Nice to Have:

• Gen AI experience: 3+ years of experience developing products with, and guardrails for, LLMs strongly preferred
• ML Infrastructure: Hands-on experience with developing, deploying, and maintaining ML infrastructure, including model training, evaluation, and deployment. Familiarity with MLOps tools and concepts including MLFlow, AWS Sagemaker, model registries, and CI/CD
• No-Code AI Tools: Experience support end users of no-code AI-assistive tools and platforms and ability to support transitions of no-code prototypes to dev and production environments
• Cloud Services: Practical experience with cloud services such as AWS (preferred), Azure, or Google Cloud for deploying and managing AI/ML workflows and containerization tools like docker
• Data Engineering: Familiarity with data engineering concepts and tools, including data pipelines, ETL processes, data warehousing, the medallion architecture, and dbt

What we offer:

As a mission-driven global company, Harvard Business Publishing is committed to fostering a culture of inclusion, trust, and engagement where everyone is welcome, valued, respected, and feels they belong. In addition to a competitive compensation and benefits package, we offer meaningful programs focused on career development and employee wellness, such as education reimbursement and early-release Summer Fridays!

HBP is 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.

$125,000 - $140,000

Above is the annualized pay range for this position. In addition, this position includes the opportunity to earn our annual Performance Based Variable Pay Program. Actual salary will be set based upon a range of factors, including external benchmark market data, individual knowledge, skills, experience, location and internal equity.