Senior Executive - Data Science & Analytics

What Will You Do?

• Model Development: Build analytical models such as forecasting, optimization, and recommendation engines using user, behavior, and consumption data to enhance the end-user experience. Develop and refine sophisticated AI models focused on audio and video data to improve content quality. Apply advanced analytics to decode social media data from platforms like Instagram, Facebook, and Twitter using sentiment analysis, theme generation, and Named Entity Recognition (NER) for deeper insights.
• Technology Application: Demonstrate working knowledge of cutting-edge technologies such as large language models (LLMs) and generative AI (GenAI, and apply them practically.
• Code Development: Write modular, efficient code to streamline the production and deployment of models.
• Analytics Delivery: Provide top-tier analytical capabilities and ensure best-in-class analytic service delivery for business initiatives. Proactively identify new opportunities and problems that can be addressed through analytics, showcasing an entrepreneurial mindset.
• Project Management: Structure business problems into analytical problems, set up model frameworks by identifying relevant approaches and techniques, and drive implementation. Lead and liaise with business and other stakeholders, discussing, presenting, and concluding projects.
• Agile Process Deployment: Implement an agile process for analytics, including generating hypotheses, running experiments, and sharing outcomes/insights with the business.
• Model Maintenance: Support the deployment, maintenance, and ad-hoc analysis required for existing or new analytical models. Ensure appropriate capture of data sources and metrics to share across the enterprise.

Who Should Apply for this role?

• Educational Background: Graduate or Master's degree in engineering, math, statistics, economics, business analytics, or a relevant quantitative discipline. Strong academic performance with emphasis on analytics and business applications is required.
• Experience: 0 to 3 years of experience in advanced analytics, including predictive analytics, statistical analytics, clustering, and segmentation. Demonstrated expertise in handling audio and video data, with experience in building models for Automatic Speech Recognition (ASR), Text-to-Speech (TTS), Speech-to-Text (STT), and leveraging Large Language Models (LLMs) and Generative AI (GenAI).
• Technical Skills: Strong knowledge of statistics with experience in techniques such as segmentation, clustering, multivariate regression, decision trees, forecasting, time series, nonlinear modeling, and optimization models. Proficiency in statistical programming tools like R/Python is essential. Ability to extract, aggregate, structure, and manage large data sets using database querying languages such as SQL. Experience with big data platforms and tools (e.g., Hadoop, HDFS, Hive, Pig, Cassandra, Storm) is preferred but not mandatory. Working knowledge of digital analytics tools such as Site Catalyst, Web Trends, Google Analytics, and Omniture is desired but not mandatory.
• Personal Attributes: An excellent problem solver with a research-oriented approach. Proactive, with a strong desire to learn and continuously improve.