Data Science Lead - Predictive Analytics & Machine Learning (10-17 yrs)

Responsibilities :

The incumbent will lead a team of data scientists and campaign managers. S/He will work closely with cross functional teams like Subscriber Marketing, Content, Product, IT, Tech, and Customer Operations to identify & solve key business problems. Key responsibilities for this position are listed below:

- Leverage Gen AI for Transformational initiatives at across various offerings - DTH, mobile app.

- Building and improving Recommendation Engines, Propensity Modelling, Unsupervised Learning, Fraud Detection, Patterns & Visualisations

- Improving the Quality, Performance and Effectiveness of the campaigns

- Working on various statistical and data science models to test and evaluate them

- Evaluating models and predict performance of data science models using ROC curve and Lift Analysis

- Providing expertise to the organisation on statistical techniques

- Building deep learning based complex systems utilising structured and unstructured data

- Setting up and manage a team of data scientists and campaign managers

- Collaborating with data engineering team on building data marts, reports, data warehouse, data pipelines and data tracking mechanisms

- Micro segment the base for better upsell of content. Leverage AMS (Audience Measurement system).

- Integrate data science models into various campaigns

- Manage various segmented upselling and retention campaigns which will be administered through various modes of communication e.g. outbound, TV channels, SMS, emails, App Notifications, website etc

The Person :

- 10+ years in the Data Science and Analytics domain

- Expertise in Predictive Analytics & Machine Learning concepts like such as regression, classification, SVM, recommendation engines, neural network etc.

- Hands On experience to open source analytical tools - such as R, Python

- Hands On experience of data visualization tools like Tableau

- Experience of working on web analytics using tools like Mix Panel for analytics and experimentation

- Exposure to implementing data science solutions in production environments

- Exposure to Gen AI technology for solving business problems like NLU Search, CVM, Metadata enrichment etc.

- Understanding of analytical architecture components; query languages, web services, APIs etc

- Experience working on cloud and it's components: AWS / Azure / Google Cloud Platform (any one)

- Experience working on Big Data technologies like Spark, PySpark, SparkR etc

- Proven experience in Model to Market

- Good understanding of commercial (revenue and retention) aspects of the business.

- Experience of leading and driving multiple complex projects with a sharp customer-focus

- Sound problem identification, judgment, resolution and decision-making skills

- Innovation oriented and a proponent of disruptive and out-of-the-box thinking

- High level of integrity, ownership and accountability

- Excellent written and verbal communications; ability to articulate thoughts clearly and concisely; excellent interpersonal skills.