Job Description

To be “a data driven organization” is one of the key themes on which the organisation aims to achieve Goal 2025. Consequently the role of advanced analytics has to scale up to be able to deliver significant business outcomes.

This is an opportunity to be a part of the data science team who work very closely with business today. The team has already successfully delivered small scale machine learning campaigns and also forayed into predictive modeling in health analytics. The ambition is to scale up data science so as to be able to contribute significantly towards Income’s Goal 2025.

We are looking for a talented data scientist who looks at data analytics as both science and art. Someone who is excited about feature engineering and is outcome focused. This is an exciting journey for someone who is pro-active and passionate about problem solving.

Key responsibilities include:

• Work with stakeholders across the organization to identify opportunities for leveraging data to drive business solutions.
• Analyze, develop and deploy machine learning and optimization models for enhancing upsell/ cross sell, improving customer segmentation, aid product development, marketing techniques and business strategies.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom data models and algorithms to aid solving business problems.
• Ideate and develop A/B testing frameworks for testing business hypothesis and testing model quality.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Develop processes and tools to monitor and analyze model performance and data accuracy.
  

• Maths / Economics / Analytics related qualification or if candidate has very relevant work experience)
• 2-3 years’ experience in an analytics role with some specific experience in advanced analytics project. Experience in financial industry (bank/insurance) will be at an advantage but other analytics intensive industries like telecom will also be considered.
• Experience in statistical modeling, machine learning, data mining, unstructured data analytics in corporate and/or academic research environments
• Experience in statistical and other tools/ languages – e.g. R, Python, SQL, Tableau, Java, Scala
• Good familiarity with relational databases and hadoop infrastructure
• Hands on experience in classification models, cluster analysis, neural network, non-parametric methods, multivariate statistics
• Aptitude to learn, think creativity to solve real world business problems, and work in a collaborative team environment