Assistant Manager - Marketing Analytics and Data Science

About the Company

Originating from a single idea, the company has empowered travelers with seamless and immediate travel booking options, offering extensive choices. Established in 2000, it initially catered to the US-India travel market with value-driven products backed by technology and customer support. The firm expanded into India in 2005, supporting low-cost carriers and offering flight, hotel, and holiday package bookings. It has grown partnerships across aviation, hospitality, homestays, villas, and expanded services to ground transport, including cabs, buses, and train bookings. New initiatives such as a business travel suite and a platform for travel agents have also been launched, along with entry into the Gulf market with competitive flight and hotel deals.

Role Overview

The Marketing team shapes brand perception and drives customer acquisition through diverse channels including brand, performance, CRM, mobile, and digital marketing. The Marketing Insights & Analytics group underpins these efforts by enabling data-driven decision-making, setting key performance metrics, performing analytics and attribution modeling, customer segmentation, and optimizing channels to enhance marketing performance and ROI.

The role focuses on addressing challenging marketing and business issues using advanced analytics and data science methodologies. The position requires mastery of SQL, Python, and the development and deployment of statistical and machine learning models that generate tangible business outcomes. The role entails transforming undefined business challenges into methodical analyses, conducting comprehensive root cause analysis, and collaborating with marketing, product, and business units to create scalable data-driven solutions that boost performance and customer satisfaction.

Key Responsibilities

• Analyze large datasets daily to identify trends, patterns, and derive actionable insights.
• Perform in-depth root cause investigations employing statistical approaches, hypothesis testing, and time-series or comparative methods.
• Construct automated data workflows and pipelines utilizing SQL and Python.
• Design, develop, validate, and operationalize statistical models and machine learning algorithms for classification, regression, forecasting, and clustering.
• Manage end-to-end data science projects from problem definition through deployment, including continuous monitoring of model performance.
• Partner with engineering teams to productionize models and implement effective tracking systems.
• Create optimized, scalable SQL queries for data extraction, transformation, and data quality assurance.
• Develop reusable analytical tools, frameworks, and scripts in Python.
• Generate automated dashboards and reports to communicate insights to stakeholders clearly.
• Work collaboratively with product, marketing, operations, and leadership to convert business challenges into structured analytical projects.
• Offer data-backed recommendations to facilitate strategic planning, A/B testing, and ongoing optimizations.

Qualifications and Experience

• Graduate in any specialization of engineering or technology from a reputed institution.
• 4 to 6 years of professional experience in analytics, data science, or consumer insights roles.
• Advanced knowledge of Excel, SQL, and Python for complex data analysis.
• Experience with analytics platforms like Adobe Analytics, Mixpanel, or Google Analytics.
• Proven ability to collaborate effectively across different functional teams.
• Strong analytical problem-solving capability, meticulousness, and rigor.
• Demonstrated success in generating business value through data-driven insights.

Success Factors

• Expert analytical proficiency with ability to simplify complex data into clear insights and strategic recommendations.
• Adaptability to ambiguous and evolving scenarios coupled with openness to innovating with new analytic tools and approaches.
• A commercial mindset aligning analytics outcomes with business growth objectives and influencing decision-making.
• Excellent communication skills to convey complex concepts clearly and foster trust among cross-functional teams and senior management.