Senior Data Scientist - Global Innovation

Job Title: Senior Data Scientist - Global Innovation

Role-Band: 6

Location: Bangalore

Reporting to: Sr Manager, Category Management

1. PURPOSE OF ROLE

This role sits at the intersection of advanced analytics, data science, and global commercial strategy, driving the development of next-generation analytical capabilities to optimize pricing, trade investments, portfolio mix, and market execution. The position will lead the design, scaling, and automation of machine learning and statistical frameworks that enable data-driven commercial decision-making, predictive scenario planning, and real-time performance management across markets.

By integrating diverse internal and external data ecosystemsincluding transactional, market, and customer-level intelligence this role will generate actionable insights on price elasticity, promotional effectiveness, channel productivity, and category dynamics. The objective is to enable global commercial innovation, supporting smarter trade investments, stronger category strategies, and more effective go-to-market decisions that drive sustainable margin expansion, improved trade ROI, and accelerated growth across markets.

2.KEY TASKS AND ACCOUNTABILITIES

Lead the development of advanced commercial analytics solutions that support strategic decision-making across pricing, promotions, assortment, channel strategy, and go-to-market execution.

Design and scale machine learning and statistical frameworks to analyze consumer behavior, market dynamics, and commercial performance across multiple markets and channels.

Develop predictive and causal modeling capabilities to evaluate the impact of commercial initiatives, enabling data-driven optimization of trade investments, promotional strategies, and portfolio decisions.

Build demand forecasting and market intelligence models that integrate internal and external signalsincluding market data, customer behavior, and competitive activityto improve planning accuracy and strategic foresight.

Apply advanced segmentation and clustering techniques to identify growth opportunities across customers, categories, and geographies, enabling more targeted commercial strategies.

Drive scenario planning and simulation modeling to evaluate strategic business decisions under different market conditions and support forward-looking commercial strategy development.

Lead commercial experimentation and impact measurement, using structured testing frameworks and quasi-experimental methods to assess the effectiveness of business initiatives.

Integrate internal commercial datasets and external market intelligence to build scalable analytics pipelines and unified data foundations for advanced modeling and strategic insights.

Develop automated analytics workflows and executive dashboards to track commercial performance, portfolio dynamics, and strategic KPIs in near real time.

Partner closely with senior commercial leadership, finance, and regional market teams to translate analytical insights into actionable strategies and operational improvements.

Prepare and deliver high-impact insights and strategic recommendations to VP and executive stakeholders, shaping commercial priorities and innovation roadmaps.

Continuously improve model performance and scalability through advanced feature engineering, model validation, and deployment best practices.

Mentor and guide analytics talent within the team, strengthening capabilities in advanced analytics, machine learning, and business storytelling.

Maintain strong analytics governance and documentation, ensuring transparency, reproducibility, and long-term scalability of analytical solutions.

OTHER COMPETENCIES REQUIRED

• Presentation Skills: Effectively presenting findings and insights to stakeholders and senior leadership to drive informed decision-making.
• Collaboration: Working closely with cross-functional teams, including marketing, sales, and product development, to implement insights-driven strategies.
• Continuous Improvement: Actively seeking opportunities to enhance reporting processes and insights generation to maintain relevance and impact in a dynamic market environment.
• Data Scope Management: Managing the scope of data analysis, ensuring it aligns with the business objectives and insights goals.
• Act as a steadfast advisor to leadership, offering expert guidance on harnessing data to drive business outcomes and optimize customer experience initiatives. Serve as a catalyst for change by advocating for data-driven decision-making and cultivating a culture of continuous improvement rooted in insights gleaned from analysis.
• Continuously evaluate and refine reporting processes to ensure the delivery of timely, relevant, and impactful insights to leadership stakeholders while fostering an environment of ownership, collaboration, and mentorship within the team.

TECHNICAL SKILLS MUST HAVE

Data Analysis & Engineering: Strong proficiency in SQL, Python (Pandas, NumPy), and advanced Excel for large-scale data processing and commercial analytics.

Data Visualization & Reporting: Expertise in Power BI and Tableau to develop interactive dashboards and performance tracking tools.

Advanced Analytics & Modeling: Experience in regression, time-series forecasting, and machine learning models using frameworks such as scikit-learn and XGBoost.

Data Pipelines & Integration: Understanding of ETL processes and data pipelines to integrate internal and external datasets for scalable analytics.

Executive Communication & Insights: Strong executive presence with the ability to translate complex analytics into clear insights and impactful PowerPoint narratives for senior leadership and VP-level stakeholders.

3.QUALIFICATIONS, EXPERIENCE, SKILLS

Please list the following requirements

Level of educational attainment required:

• Bachelor or Post-Graduate in the field of Business & Marketing, Engineering/Solution, or other equivalent degree or equivalent work experience.
• Extensive experience solving business problems using quantitative approaches.
• Comfort with extracting, manipulating, and analyzing complex, high volume, high dimensionality data from varying sources.

Professional qualifications and accreditations/memberships required:

• MBA/Engg. in a relevant technical field such as Marketing/Finance.
• 5-8 years of experience in the Retail/CPG domain.
• Proficient in Python (pandas, scikit-learn, statsmodels) and SQL.
• Stakeholder management, and excellent interpersonal skills.

Language skills required:

• Fluent in English (Speaking, Reading, and Writing).

Technical and functional competencies:

• Proficient in Python (pandas, scikit-learn, statsmodels), SQL, and Power BI.
• Skilled in regression, Bayesian modeling, uplift modeling, time-series forecasting (ARIMA, SARIMAX, Prophet), and clustering (k-means).
• Strong grasp of hypothesis testing, model validation, and scenario simulation.

And above all of this, an undying love for beer!

We dream big to create future with more cheers.