Disha Indrakant Mishra

Senior Data Scientist - ML

CarTrade•  February 2022 - Present•  Mumbai

Working within the automobile domain, currently responsible for – Lead the design, development and deployment of our deep learning, ML and NLP solutions ● Providing actionable ad-hoc insights to stakeholders ● Improving established, advanced machine learning projects like lead forecasting ● Advanced analytical methods are used to explore and extract additional data value for existing and emerging products ● Reports and visualization tools are integrated for a holistic view as a part of a story telling experience through data

Analytics Engineer - ML

Aureus Analytics•  August 2019 - February 2022•  Mumbai

Responsible for descriptive, predictive and prescriptive analytics for clients in the insurance domain Few responsibilities - ● Work closely with business users to understand their business problems, evaluate data sources and suggest data science based solutions to solve them ● Use key insights and build analytical predictive models to help solve business problems faced by the insurance companies – life and general LOBs ● As a part of the RnD projects, was instrumental in conceptual designing of the company’s product – SentiMeter v2.0 and development of a working prototype using text analytics, adding a layer of NER.

Specialist - Data Science

Reliance Health Insurance Ltd•  September 2018 - August 2019•  Mumbai

Experience in customer / stakeholder management with problem solving Responsibilities (Briefly) - ● Work with stakeholders throughout the company to identify opportunities and leverage company’s limited data to drive the business solutions ● Use techniques to increase and optimize business functioning ● Design the analytics roadmap for stakeholders

Analyst - Analytics Solutions

Hansa Cequity•  September 2016 - September 2018•  Mumbai

Experience in performing descriptive, predictive as well as prescriptive analytics for BFSI Domain. ● Responsible for building and implementing statistical models and performing descriptive analysis to gather key insights for leading BFSI Clients – Banking and Insurance Industry ● Worked on POCs that enabled the company increase their clientele Banking Industry: ● Conducted predictive analytics by building machine learning models (sales, cross-sell and retention) using various statistical techniques on huge data sets with a very low event rate and high accuracy; later implementing them by creating stored, scheduled procedures ● Performed prescriptive analytics by designing marketing strategies with the help of insights obtained through analysis ● Communicated the insights in a compelling manner using visualization tools and dashboards for the business Insurance Industry: ● Performed descriptive analytics by mining huge data sets to capture notable trends and generate insights for client ● Built an upsell model to help company generate business through their existing customers and the orphan customers; 90% actual upsell customers belonged to the model identified priority 30% base ● Assisted in developing the retention revenue models – lapsations and fraudulent claims ● Carried out prescriptive analysis of the customers for identifying the quality of the customer portfolio of the company ● Built a surrender model for another insurance client to help them identify high propensity customers and apply appropriate business strategies to retain them. Through the model, by targeting only 30% policies, approx. 8000 surrenders were prevented, based on priority and ticket size