Data Scientist

Who You'll Work With

Embark on a challenging yet rewarding career path focused on driving lasting client impact and building long-term capabilities. Thrive in a high-performance culture that values resilience, determination, and continuous learning. At McKinsey, we invest deeply in your development, offering unparalleled resources, mentorship, and opportunities to accelerate your leadership journey. Expect apprenticeship, coaching, and exposure that foster rapid growth. Our culture emphasizes continuous learning through structured programs and actionable feedback, encouraging you to embrace challenges and own your development. Your voice matters from day one; we value your innovative ideas and contributions, upholding ethics and integrity while celebrating diverse perspectives to achieve optimal outcomes. Join a global community of over 100 nationalities across 65+ countries, fueling creativity and delivering exceptional solutions for our clients.

Your Impact

As a Data Scientist with the Periscope initiative at McKinsey & Company in Bengaluru/Bangalore, India, you will collaborate with the Insights & Analytics group and consulting teams to address complex client challenges, particularly within the marketing domain. You will apply and administer analytical and modeling tools and techniques, deriving valuable insights through statistical methods and predictive modeling. Your primary focus will be client service, complemented by contributions to knowledge development. Key responsibilities include performing statistical analysis and modeling for marketing efforts, developing models to optimize pricing and promotions, guiding analytics projects, supporting the development of proprietary McKinsey marketing techniques, coaching new hires, and delivering high-quality end products punctually, with rigorous quality checks.

You will work closely with the Growth, Marketing & Sales (GM&S) team, primarily supporting the Insights & Analytics (IA) group. GM&S leverages McKinsey's extensive marketing and sales expertise to help leading companies enhance pricing, promotion, assortment strategies, and performance management. Through integrated data warehousing and intuitive interfaces, clients gain granular insights into their commercial and financial performance, enabling data-driven decision-making and the embedding of new commercial capabilities. GM&S champions innovation in analytics, design thinking, mobile, and social technologies, fostering an entrepreneurial culture and driving asset-based consulting through innovative SaaS solutions, strategic acquisitions, and a robust partner ecosystem.

Your Qualifications and Skills

• Hold a Bachelor's or Master's degree in computer science, applied statistics, mathematics, engineering, or a related field.
• Possess 2+ years of in-depth technical experience in advanced analytics, statistics, and machine learning.
• Demonstrate hands-on experience in building, training, and optimizing predictive models, with a strong ability to interpret and evaluate results.
• Knowledge of hypothesis testing and experimental designs, such as A/B testing, is advantageous for investigations and recommendations.
• Exhibit advanced Python expertise, including proficiency with key libraries like Pandas, NumPy, Scikit-learn, Matplotlib, and Seaborn; Kedro familiarity is a plus.
• Proven capability to efficiently manage large datasets, including data cleaning, transformation (feature engineering), and analysis, while ensuring data quality and integrity.
• Proficiency in SQL, with the ability to write intermediate-level queries for data extraction and transformation.
• Strong understanding of cloud platforms, specifically AWS and/or Azure Databricks.
• Familiarity with data visualization tools like Tableau or Power BI, and version control systems such as Git, is highly desirable.
• Intermediate expertise in Excel for presenting outputs and building basic models for scenario analysis and decision-making.
• Possess excellent presentation and communication skills, with the ability to articulate complex analytical concepts and insights to both technical and non-technical audiences.