Data Scientist – Customer Analytics

About the job

Job Summary We are seeking a highly analytical and business-savvy professional in Customer Loyalty & CRM function to drive customer analytics initiatives and strategic decision-making. The ideal candidate will have a strong background in data analysis, customer segmentation, and predictive modeling, with a proven ability to translate insights into actionable business strategies. Key Responsibilities: • Analyse customer behaviour across booking, travel, and loyalty lifecycle to identify actionable insights. • Develop and refine segmentation models to support targeted campaigns and personalized offers. • Drive member engagement, tier movement, redemption patterns, and breakage analysis. • Design and implement dashboards and reports to monitor key customer metrics (CLTV, CAC, NPS, etc.). • Build predictive models for churn, upsell, cross-sell, and reactivation strategies. • Support strategic initiatives such as dynamic pricing, ancillary revenue optimization, route-level customer insights and campaign performance. • Conduct deep-dive analyses to uncover insights on customer journeys, conversion funnels, and campaign performance. • Drive experimentation and A/B testing to optimize customer engagement and experience. Required Skills And Experience: • 6–8 years of experience in customer analytics, marketing analytics, or related fields. • Strong proficiency in SQL, Python/R, and data visualization tools (Tableau, Power BI, etc.). • Experience with statistical modeling, machine learning, and data mining techniques. • Solid understanding of customer lifecycle metrics and marketing KPIs. • Familiarity with customer data platforms (CDPs) and CRM tools. • Ability to translate complex data into clear business insights and recommendations. • Excellent communication and stakeholder management skills. Good To Have: • Strong proficiency in SQL, Python/R, and data visualization tools (Tableau, Power BI, etc.). • Experience with statistical modeling, machine learning, and data mining techniques. • Familiarity with customer data platforms (CDPs) and CRM tools. Educational Qualifications: Bachelor’s or Master’s degree in Statistics, Economics, Data Science, or a related field. Akasa Air does not solicit or accept any form of payment from candidates or institutions during its recruitment process. Any such claims are fraudulent and should be disregarded. Individuals engaging with unauthorized entities do so at their own risk. We encourage you to report any such incidents to info@akasaair.com for appropriate action.

Requirements

• data analysis
• customer segmentation
• predictive modeling
• SQL
• Python
• data visualization
• statistical modeling
• machine learning
• data mining
• communication

Qualifications

• Bachelor’s degree
• Master’s degree
• Statistics
• Economics
• Data Science

Preferred Technologies

• data analysis
• customer segmentation
• predictive modeling
• SQL
• Python
• data visualization
• statistical modeling
• machine learning
• data mining
• communication