Data Scientist

Data Scientist

This role is pivotal in understanding customer behavior and translating business challenges into intelligent analytical solutions. The ideal candidate will combine deep expertise in predictive modelling, AI/ML, and conversational AI with strong business engagement skills to deliver impactful, technology-driven solutions that enhance customer experience and drive business growth.

• MBA/Masters in a quantitative discipline like Mathematics/Statistics/Operations Research/Computer Science/Economics/Engineering or B-Tech in any related engineering discipline
• The ideal candidate should have 3+ years of experience in the Marketing Analytics domain with a strong foundation in analytical thinking and problem-solving. 
• They must possess proven technical expertise in AI/ML modelling, including propensity and predictive modelling, along with hands-on experience in LLM-based Chatbot Development and Conversational AI. 
• The candidate should be proficient in Python and SQL, experienced in working with GCP and BigQuery, and capable of building dashboards using Power BI or Qlik Sense. 
• Strong understanding of Digital Marketing and Customer Analytics, combined with data handling and ETL processes, is essential. 
• Above all, the candidate must demonstrate the ability to confidently engage with business stakeholders and deliver technology-driven solutions that create measurable business impact.

• Strategic Business Partnership: Collaborate closely business stake holders to deeply understand business challenges, define key performance indicators (KPIs), and translate complex customer-focused questions into clear, actionable analytical requirements. Act as a trusted analytics advisor to business teams, proactively identifying opportunities where data and AI can solve real business problems.
• Customer Insight & Propensity Modelling: Conduct in-depth analysis of customer behavioural data to identify trends, patterns, and opportunities. Design, develop, and deploy propensity models (e.g., purchase propensity, churn prediction, upsell/cross-sell likelihood, lead conversion likelihood) using advanced statistical and machine learning techniques. Translate model outputs into actionable business recommendations.
• AI Chatbot Development & Optimization: Lead the design, development, and continuous improvement of AI-powered chatbot solutions to enhance customer engagement and automate customer interactions. Collaborate with product and technology teams to integrate NLP/NLU capabilities, define conversation flows, and measure chatbot effectiveness through relevant KPIs.
• BI & Data Product Development: Build, maintain, and optimize interactive dashboards and reports using BI tools (e.g., Power BI, Qlik Sense) to visualize customer performance metrics. Develop robust and scalable data pipelines to ensure timely, accurate, and reliable data flow from various customer data sources into analytical platforms.
• Process Efficiency & Innovation: Continuously identify opportunities to enhance data collection, processing, analysis, and insight delivery workflows. Proactively research, evaluate, and implement new tools, technologies, and methodologies — including Generative AI — to increase efficiency, accuracy, and depth of analytical capabilities.
• Cross-functional Collaboration: Work seamlessly with data engineers, IT, marketing, and product teams to ensure data consistency, integrate analytical solutions, and drive data-driven decision-making across the organization. Effectively communicate complex analytical findings and model outputs to both technical and non-technical audiences.