Data Science Senior Manager

Job Description 

At our company, we hold an uncompromising stance against mediocrity, committing ourselves to work that delivers audacious impact and is fueled by a pioneering spirit of continuous progress and innovation. This ambition is supported by leadership grounded in courage and clarity—ensuring alignment, accountability, and purpose in everything we do. Integrity shapes how we hire, recognize, and develop talent, with a focus on potential, ambition, and long-term growth. Together, we operate with collective strength, prioritizing meaningful results over unnecessary rituals and navigating challenges with unity and resolve. Above all, we remain steadfast and resilient, never losing sight of our commitments and continuously pushing forward through complexity with determination and purpose to create a better life for all.

• Develop and deploy advanced machine learning and AI models for Commercial business functions and Sales function covering Price-elasticity models, Churn management, Product recommenders, ARPU growth and revenue enhancement.

• Design and operationalize GIS-driven analytics leveraging satellite imagery and diverse geospatial datasets to develop micro-granular segmentation models and opportunity clusters.

• Lead predictive analytics and prescriptive analytics across the different business verticals to forecast the impact and prescribe actions including churn prediction, revenue forecasting, usage forecasting, correlation to events, and behavioral analytics.

• Develop, optimize and maintain Commercial and Sales related AI-products (Retail stock prediction, Credit scoring, Value-based segmentation, etc) through necessary feature engineering with updated business dynamics and refitting the models.

• Translate complex analytics into clear business storytelling and actionable recommendations for C-suite, Commercial, Sales, Digital and Marketing leadership.

• Collaborate with cross-functional teams – Pricing, CVM, Product, Sales, Digital, Customer Experience, Finance, BSM and Technology – to embed data-driven decisions across the commercial value chain.

Academic Qualification

• B.Sc. in Computer Science / CSE / Applied Statistics / Mathematics or related field from a reputed university

• Master’s degree in Data Science, AI, Statistics or related field will be an added advantage

Job Experience Required

• 6+ years of total experience including at least 5 years in a relevant data science, advanced analytics or BI role

• Minimum 2-3 years of hands-on experience in machine-learning model development; telecom or large-scale customer-base experience is preferred

Required Capabilities

• Hands-on expertise in Python, R and SQL with working knowledge of RDBMS, UNIX environment and shell scripting

• Proven experience developing predictive models in customer segmentation, churn, CLM and recommendation systems using data-science tools and statistical techniques

• Strong skills in handling, cleansing and preparing large datasets for structured data modelling

• Working knowledge of data-visualization tools such as MicroStrategy, Tableau and Power BI

• Strong understanding of the Telecom industry value chain, insights and competitive dynamics

• Excellent storytelling, written and verbal communication skills, with the ability to translate complex ML/statistical results into business language for senior stakeholders