Manager/Senior Manager - Analytics/Data Science - Insurance

Our client is a global Insurance company that has an analytics team which uses all kinds of advance analytics/data science, AI/machine learning, data visualization / self-service analytics, data mining, and deep-dive insights & analysis techniques to work on many business problems. The team closely works with senior stakeholders and the management team to solve business problems and help them achieve business objectives.

They are looking for a Manager /Senior Manager to be part of the Advanced Analytics & Data Science Department. This role reports to the General Manager and is an IC role.

Key Responsibilities:

- Consulting with internal customers (e.g., Agency, Bancassurance, Operations, and other key stakeholders) to develop analyses that lead to actionable insights. (Need candidates with strong communication skills)

- Deriving data from multiple sources including sales, product, and customer databases to create integrated views that can be used to drive decision making

- Working with several large and complex data that is mined through SQL Server/Oracle

- Create predictive/propensity models using advanced / machine learning algorithms (in near future work on AI algorithms also) and tools like Python / R (Primary tool - Python)

- Generate actionable insights from the data and present them to senior stakeholder

- Create scorecards/dashboards to highlight focus areas for the business either in excel/BI/ Data Visualization tools like QlikSense

Required qualifications and experience:

- Postgraduate in Economics / Statistics / Mathematics or have done engineering with at least 6 years of experience in using advanced analytics tools/machine learning (ML) algorithms

- Should be preferably from BFSI / Retail / Telecom domain. Prior Insurance domain knowledge or work in Insurance Analytics would be an added advantage

- Should have worked with senior business stakeholders & functional teams to build, test & validate various hypotheses and build actionable insights

- Need to be strong in quantitative analysis & coding. Should have practical knowledge of creating a Predictive / Propensity Model, clustering/segmentation, up / cross-sell. Should be experienced in using supervised and unsupervised machine learning techniques like Gradient Boosting, XG Boost, LGBM, Random Forest, Logistic Regression, Decision Tree, K-Means Clustering, etc.

- Prior experience on working on Insurance business problems like Early Claims, Claims Fraud, or building Cross/ Up-Sell models would be given priority

- Should be well versed with Python

- Strong presentation skills including making presentable PPTs

- MS Office - Excel / Access / PowerPoint / Office

Knowledge and skills desired :

(A) Technical Skills

a. Statistical knowledge

b. Dealing with varieties of data - Knowledge of data models in Oracle/SQL Server would act as a strong plus point

c. SQL expertise and data pre-processing in Python or other languages

d. Strong working knowledge of Python, SQL

e. Data science conceptual understanding

f. Data science practical experience

g. Working knowledge of Big Data tools like Hive, Pyspark, Scala would be an added advantage

(B) Soft Skills

a. Analytical, creative, and innovative approach to solving problems

b. Strong written and verbal communication

c. Strong presentation skills

d. Entrepreneurial spirit - You are part of the setup team!

e. Understanding customer life cycle and data lineage is an added advantage