Senior Manager, Insights Data Science, Private Equity

Key Skills

Java Programming, Analytical and Problem solving, Design, Risk Analytics, Python Programming, Database, SQL, PowerBI, Machine learning techniques, Data science techniques, Alteryx, Data Visualization, Looker, Pandas, QlikView, Tableau, Snowflake, Algorithms, Amazon RedShift, PySpark, R-Shiny, Statistical modeling, Sensor fusion Algorithms, Data pipelines, Geopandas

Job Description

Bain's Advanced Analytics Group (AAG) leads the firm's advanced analytics efforts and analytical advisory for clients globally. The team helps our clients extract maximum value from their data assets, regardless of location or format. AAG applies the latest analytics techniques and tools to help generate insights that yield better & faster decisions ranging from customer experience and predictive NPS to enhanced go-to-market strategies and improved employee engagement.

Within AAG there is a dedicated team that concentrates on the use of advanced analytics in Private Equity (PE). The focus of this AAG PE team primarily concentrates on due diligences, vendor due diligence and post-acquisition value creation, with a mix of supporting client facing work and developing new cutting-edge tools and approaches.

You will work as part of the AAG PE team, leading the regional AAG PEG ringfence of data scientists. On client assignments, you will work together with AAG leaders and generalist consulting teams on challenging and exciting analytical problems that are common in the different stages of Private Equity projects. You will also lead the team together with a generalist consulting side Expert Senior Manager, both in strategy (e.g. industries to target, new tools / use cases to develop, team growth, support resources required as team grows) and operations (e.g. recruiting, staffing, professional development).

WHAT YOU'LL DO

• Work with Private Equity teams to understand business problems, translate them into analytics projects and appropriately prioritize and execute
• Collaborate with Bain’s Private Equity Group leadership and the other AAG Private Equity regional leads to ensure Bain remains cutting edge in using analytics to solve our clients problems
• Work with PE stakeholders to identify industries to target, ideate and prioritize, and then oversee the development of new AA tools and approaches for Private Equity cases
• Train the AAG PEG ringfence (consists of rotating and permanent members) to onboard new team members, up-skill to best support PEG case work, share insights and learnings
• Drive the team operations (e.g. recruiting, staffing, professional development), with support from Expert SM, other SMs in the team, and dedicated Operations resource as needed
• Develop relationships with external data and analytics vendors and interact as needed
• Help to increase consulting staff’s knowledge of Advanced Analytics and how it can be used in a PE environment

Some examples of analytical methods that the team will be using on such projects are the following (not exhaustive):

• Integrate and wrangle with data that comes from different sources to extract critical insights which are required for valuations of companies
• Use location intelligence to make conclusions around how many new stores a deal target can expect to build, and where
• Build dynamic data visualization tools on operational data, which help in doing thorough performance assessments
• Analyze large amounts of transactional data to e.g. measure cross-sell or up-sell potential, understand and measure the size of the most typical consumer cohorts, assess churn, and ultimately help funds decide on risks or potential upsides
• Analyze e-commerce data to understand market dynamics of product categories and consumer behavior
• Define consumer segmentations based on primary research data
• Forecast the performance of a market going forward
• Predict adoption of new products / services based on past, current and predicted future adoption from primary / secondary research
• Coordinate with internal and 3^rd party data providers for sourcing of critical data elements
• Establish automated data pull pipelines to accelerate the speed at which Bain delivers insights

ABOUT YOU

We are looking for someone who has:

Essential skills

• 7+ years of experience in addressing business needs through data analytics
• 1+ year working in Private Equity
• Proven passion for analytics and Business Intelligence, and a keen interest in the practical insights driven by the analytics
• Interest in building deep expertise in Private Equity
• Extensive knowledge of data visualization design principles
• Intermediate experience with commercial business visualization platforms such as Tableau, PowerBI, Qliksense, Looker etc.
• Experience with at least one low code data wrangling platform such as Alteryx, MS PowerQuery, TableauPrep, KNIME or RapidMiner
• Intermediate SQL knowledge and flexibility in using these skills in different database environments (AWS Redshift, Snowflake, etc.)
• Intermediate Python skills with a focus on data integration and transformation (e.g. Pandas, PySpark, etc.).
• Basic knowledge in classical statistical modelling and machine learning algorithms
• Ability to analyze and solve problems methodologically
• Ability to multi-task under pressure while maintaining a professional, customer-focused attitude
• Team orientation with ability to work autonomously
• Efficiency, accuracy and commitment to meeting deadlines
• Excellent communication and listening skills
• Outstanding organization, prioritization and time management skills
• Aptitude for practical and innovative problem solving with good attention to detail
• Aptitude for developing new products (tools / approaches) to address business questions in more advanced mannerProactive approach to learning and personal development
• Openness to giving and receiving feedback
• Business fluent / C1 English

Desired skills

• Knowledge in location intelligence analytics (e.g. GeoPandas)
• Experience in building data visualization tools on open source platforms such as R-Shiny, Python-Dask or Streamlit
• Experience in building and scaling a data science team
• Fluency in one of the following languages: German, Spanish, French, Arabic a plus.