Lead Data Scientist - Life Insurance

- Professionals in this group are responsible for developing large scale & high impact analytical / data science products to understand & derive insights from structured & unstructured data using scientific methods, processes, algorithms and systems.

- They build metaheuristic algorithms to derive optimal data insights, multi level forecasting algorithms to predict user trends and are responsible for implementation of end to end data science products. They should have extensive knowledge & experience of Data & Machine Learning Algorithms, Deep Learning algorithms and statistical libraries.

- They should have hands on experience on techniques such as user profiling, optimization, pattern mining / detection, classification / regression modelling, recommender systems & deep learning models etc.

Key Responsibilities:

Responsibilities:

- Participate in discussions with stakeholders to understand requirements.

- Process and verify the integrity of data used for analysis.

- Assist in formulating and conducting guided, multifaceted analytic studies against large volumes of data.

- Build predictive models and machine learning algorithms.

- Assist in utilising models and algorithms to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy.

- Analyse large amounts of data points to discover trends and patterns.

- Implement new statistical or other mathematical methodologies as needed for specific models or analysis.

- Implement analytical models into production by collaborating with software developers and machine learning engineers.

- Create automated anomaly detection systems and constant tracking of its performance.

- Communicate analytical solutions to stakeholders and implement improvements as needed to operational systems.

- Monitor and track the team's achievements and key performance indicators

- Develop learning roadmaps to support the professional development of the team Specific Authorities( Financial & Non Financial)

Key Performance - Create various machine learning-based tools or processes.

Internal :

Indicators - Identify and analyse problems and determine root causes.

- Build data products to extract valuable business insights.

- Enable smarter business processes-and implement analytics for better business decisions.

- Ensure compliance to release deadlines as per stakeholder (both internal and external) timelines.

Job Requirements

Qualifications

- A Bachelor's or Master's degree in data science, computer science, statistics or a related field.

- Technical knowledge

- Knowledge in atleast one of the following languages: (R, Java, Python, SQL, C/C++)

Experience

- 4+ years' full-time experience in data science.

- 3+ years of coding experience with modern programming languages such as Python, Java, C/C++.

- Data Science fundamentals in Machine Learning, Big Data, Data Visualization, Statistical analysis and computing.

- A strong track record of project delivery