Senior Data Scientist

Bain Capital Overview:

With approximately $215 billion of assets under management, Bain Capital is one of the world’s leading private investment firms. We create lasting impact for our investors, teams, businesses, and the communities in which we live. Over four decades we have strategically grown our platform to focus on Private Equity, Growth & Venture, Capital Solutions, Credit, and Real Assets. Today, our team includes 1,985+ employees in 24 offices on four continents. 

We partner differently to help people and companies embrace possibility and realize potential. Founded as a private partnership in 1984, we have fostered a culture of innovation, entrepreneurialism, and agility, empowering our people to define and own their career trajectories. Today, our partnership approach enables us to pursue strategic growth, build enduring relationships with a robust external network, and collaborate across our integrated platform to connect the deep and diverse expertise that unlocks breakthrough insights.

Our people are the heart of our advantage. Colleagues at all levels have a seat at the table as they tackle business challenges with a principal investor mindset. By asking incisive questions, respectfully challenging one another, and remaining intellectually agile, we work together to achieve exceptional outcomes. 

For more information visit: Bain Capital

Position Overview

We are seeking a highly motivated Senior Data Scientist to join our Data Science & AI team. In this role, you will partner closely with investment professionals across Bain Capital to design, build, and deploy models that power investment decision-making and generate actionable insights throughout the firm. You will be responsible for maintaining and continuously improving production models, ensuring their alignment with evolving business needs.

A successful candidate will excel at translating business problems into robust technical solutions, combining strong analytical skills with sound business judgment. You should be passionate about communicating complex findings clearly and collaborating with stakeholders at all levels.

Responsibilities

• Model Development & Deployment: Collaborate with investment teams to design, build, and deploy predictive and explanatory models that inform critical investment decisions.
• Productionization & Maintenance: Implement models in production environments; monitor, maintain, and enhance model performance and reliability over time.
• Business Problem Translation: Engage with business stakeholders to understand challenges, formulate analytical approaches, and translate needs into effective data-driven solutions.
• Data Visualization & Analytics: Develop compelling dashboards and visualizations to deliver insights and support decision-making.
• Continuous Improvement: Stay abreast of advancements in data science, machine learning, and analytics; proactively recommend and implement improvements to existing workflows and models.
• Stakeholder Communication: Communicate technical concepts and analytical findings to both technical and non-technical audiences; advocate for data-driven decision making across the organization.
• Cross-Functional Collaboration: Partner with data engineering teams to design, implement, and optimize robust data pipelines and infrastructure, ensuring reliable, scalable access to high-quality data for modeling and analytics.

Required Skills

• Proven experience designing, building, and deploying models for real-world business applications, ideally in fast-paced, high-stakes environments.
• Deep expertise in Python and SQL for data analysis, modeling, and workflow automation.
• Strong foundation in both predictive (e.g., regression, classification, forecasting) and explanatory (e.g., causal inference, interpretability) modeling techniques, leveraging standard ML and statistical libraries (e.g., scikit-learn, XGBoost, statsmodels).
• Exceptional communication skills, with the ability to distill complex technical concepts for diverse audiences.
• Experience working with generative AI models to develop, evaluate, and deploy solutions that leverage text, image, or other unstructured data.
• Expertise in data visualization and analytics, with hands-on experience using BI tools (e.g. Tableau or Sigma) to interface with business users.
• Experience productionizing models and working within modern data science toolchains, using tools such as MLflow, Airflow, or similar for workflow management and monitoring.
• Strong business judgment, intellectual curiosity, and collaborative spirit.