Lead Assistant Manager

Responsibilities

• Analyze large amounts of data/transactions to derive business insights and create innovative solutions/models/strategies.
• Aggregate and analyze internal and external risk datasets to understand performance of fraud risk at customer level.
• Analyze customer's banking/transaction behaviors, and be able to build predictive models (simple ones like logistic regression, linear regression) to predict churns or negative outcomes or running correlation analysis to understand the correlation.
• Develop personalized segmentations and micro-segmentation to identify customers based on their fraud risk, banking behaviorals, and value.
• Conduct analysis for data driven recommendations with reporting dashboard to optimize customer treatment regarding friction reduction and fund availability across the entire banking journey.
  

Skillset

• Analytics professional preferably with experience in Fraud analytics.
• Minimum 2 years of experience in relevant domain - Data Analysis and building models/strategies.
• Strong knowledge and working experience in SQL and Python is a must.
• Experience analyzing data with statistical approaches with python (e.g. in Jupyter notebook): for example, clustering analysis, decision trees, linear regression, logistic regression, correlation analysis
• Knowledge of Tableau and BI tools
• Hands-on use of AWS (e.g. S3, EC2, EMR, Athena, SageMaker and more) is a plus
• Strong communication and interpersonal skills
• Strong knowledge of financial products, including debit cards, credit cards, lending products, and deposit accounts is a plus.
• Experience working at a FinTech or start-up is a plus.
• Notice period : Max 60 days. immediate joiners preferred.
  

Education

• Bachelors or Masters in Quantitative field such as Economics, Statistics, Mathematics
• BTech/MTech/MBA from Tier 1 colleges (IIT, NIT, IIM)