Manager/Senior Manager- Data Analytics

Bandhan Life; United States; Remote; USD 80,000 - 120,000; Full time

Job summary

Join a forward-thinking company as a Data Scientist, where your expertise in data science and AI will drive impactful solutions in the life insurance sector. You'll collaborate with diverse teams to tackle complex business challenges, enhance customer acquisition, and optimize operations through advanced analytics. This role offers a unique opportunity to shape the future of life insurance, making it more accessible and efficient for everyone. If you're passionate about leveraging data to create tangible business outcomes, this is the perfect opportunity for you.

Qualifications

• 4-8 years of hands-on experience in advanced analytics and data science.
• Proficiency in SQL and Python with relevant libraries.
• Experience in insurance, banking, or FinTech preferred.

Responsibilities

• Drive data-driven strategy and solve business problems using data science.
• Collaborate with cross-functional teams to build predictive models.
• Analyze structured and unstructured data for actionable insights.

Skills

Advanced Analytics

Data Science

Predictive Modeling

Machine Learning

AI

SQL

Python

Statistical Analysis

Education

Bachelor's in Engineering

MBA

Tools

Amazon Web Services

Google Analytics

Google Cloud

BigQuery

Job description

This is a high-impact role for someone who thrives at the intersection of data science and business strategy, and is passionate about applying AI to make life insurance more accessible, personalized, and efficient.

A skilled and business-oriented Data Scientist will join the Data Science & Analytics team to drive data-led decision-making across the life insurance value chain. The role involves solving key business problems such as improving customer acquisition, underwriting, cross-sell, persistency, and claims using advanced analytics, AI, and GenAI.

The candidate will collaborate with cross-functional teams including Product, Sales, Marketing, Risk, and Actuarial to build predictive models, segment customers, optimize campaigns, and design intelligent automation solutions. Extracting insights from complex datasets, creating machine learning pipelines, and deploying scalable models that impact business growth and efficiency are core responsibilities.

Key Focus Areas:

1. Driving data-driven strategy and solving business problems using data and decision science.
2. Participating in key decision-making processes to shape the company's competitive positioning.
3. Developing analytical solutions and structured approaches to address complex business challenges.
4. Identifying friction points for customers and proposing innovative solutions.
5. Analyzing structured and unstructured data to generate actionable insights for business steering.
6. Collaborating with stakeholders across Product, Marketing, Sales, Risk, Underwriting, Customer Service, and Actuarial teams to leverage data and AI for tangible business impact.
7. Developing statistical, predictive, ML, GenAI models as needed to solve specific business problems.

Qualifications & Competencies:

1. A problem solver at heart, a first-principles thinker who enjoys challenging the status quo and devising non-traditional solutions. Loves working with numbers, technology, and has a bias for action.
2. 4-8 years of hands-on experience in advanced analytics, data science, and predictive modeling/ML/AI & GenAI.
3. Proficiency in SQL, Python, and relevant libraries for statistical data analysis and modeling.
4. Good understanding of statistics and predictive modeling concepts.
5. Experience with Amazon Web Services (Lambda, SNS, SQS, RDS, EC2, KMS, etc.), Sagemaker, and QuickSight is preferred.
6. Experience in insurance, banking, financial services, FinTech, or HealthTech is preferred.
7. Understanding of credit risk assessment, risk scoring, credit profiling & segmentation, dynamic pricing based on risk profile, and fraud prevention is advantageous.
8. Knowledge of Google Analytics, Google Cloud, and BigQuery is a plus.
9. Minimum Bachelor's degree in Engineering, Technology, Statistics, or an MBA from a reputed B-school.