Associate - Platform Data Science (Data Business CoE)

Who you will work with Bain & Company is the leading consulting partner to the private equity industry and its stakeholders. PEG (Private Equity Group) in Bain provides comprehensive advisory services to investors across the entire investment lifecycle. PEG expertise spans from pre-investment strategy and due diligence to post-acquisition value creation and portfolio management. PIT is a specialized division dedicated to supporting the private equity sector and its stakeholders. A key area of focus is harnessing Generative AI to develop innovative solutions that streamline due diligence, automate processes, and enable data-driven decision-making. By integrating expertise in due diligence, operational improvement, and cutting-edge technologies like Generative AI, PIT empowers private equity clients to achieve superior returns and maintain a competitive edge in the market. What you ll do This is an opportunity to be a part of BCN Data business expanding science capability area. This position will be part of the PIT (PEG Innovation Team) Product Support: The team will primarily support the Beta production of AI applications for PEG (Private Equity Group) as part of Bain s DD2030 (Due Diligence 2030) initiative. Generative AI Focus: A significant portion of the work is expected to relate to Generative AI applications, pushing the boundaries of innovation in the private equity space. Broader Automation: The role may also include contributing to broader PIT automation initiatives aimed at streamlining processes and enhancing efficiency across various investment lifecycle stages. The person in this role will need to: Translate business objectives into data and analytics solutions and, translate results into business insights using appropriate data engineering, analytics, visualization & Gen AI applications Leverage Gen AI skills to design and create repeatable analytical solutions to improve data quality Design, build, and deploy machine learning models using Scikit-Learn for various predictive analytics tasks. Implement and fine-tune NLP models with Hugging Face to address complex language processing challenges Collaborate with engineering team members on design requirements to turn PoC methods into repeatable data pipelines; work with Practice team to develop repeatable and scalable products Assist with creation and documentation of standard operating procedures for repeated data processes, as well as knowledge base of data methods Keep abreast of new developments in AI/ML technologies and best practices in data science, particularly in LLMs and generative AI. About you A Bachelor s or Master s degree in in Computer Science, Artificial Intelligence, Applied Mathematics, Econometrics, Statistics, Physics, Market Research, or related field is preferred 3-5 years of experience with data science & data engineering with Hands-on experience with AI/GenAI tools such as Scikit-Learn, LangChain, and Hugging Face Experience designing and developing RESTful and GraphQL APIs to facilitate data access and integration. Proficiency with data wrangling in either R or Python is required Proficiency in SQL is required, and familiarity with NoSQL data stores is a plus Familiarity with MLOps practices for model lifecycle management Experience with Git and modern software development workflow is a plus Experience with containerization such as Docker/ Kubernetes is a plus Agile way of working and tools (Jira, Confluence, Miro) Strong interpersonal and communication skills are a must. Experience with Micrsoft Office suite (Word, Excel, PowerPoint, Teams) is preferred Ability to explain and discuss Gen AI and Data Engineering technicalities to a business audience.