Data Scientist (BFS) - Banking and Financial Services

Job Description- Data Scientist (BFS) - Banking and Financial Services

Why would you like to join us?

TransOrg Analytics specializes in Data Science, Data Engineering and Generative AI, providing advanced analytics solutions to industry leaders and Fortune 500 companies across India, US, APAC and the Middle East. We leverage data science to streamline, optimize, and accelerate our clients' businesses.

Visit at www.transorg.com to know more about us.

Primary Job Location: Bangalore/Mumbai

What do we expect from you?

• Analyze & interpret data and communicate results to clients, often with the aid of

Mathematical/statistical techniques and software. This role requires:

• Data exploration, statistical/ predictive modelling, data analysis and hypothesis testing.
• Design, development and deployment of Predictive models and frameworks.
• Complex statistical concepts are explained in a way that clients can understand and advice on strategy.

What do you need to excel at?

• Well-versed in quantitative analysis, data mining, trend analysis, customer profiling, clustering and predictive modelling.
• Executing the data-driven planning process by building models and frameworks that connect business unit drivers to company financials and forecast to take the correct decision as per the business need.
• Should be able to handle assigned tasks in the capacity of individual contributor.
• Demonstrate excellent teamwork.
• Collaborate with other data analysts to provide development coverage, support, and

Knowledge sharing and mentoring of junior team members.

What are we looking for?

• Bachelor's in Computer Science, Engineering, Statistics, Maths or related quantitative degree.
• 3-5 years of relevant experience in a data analysis or related role.
• Understanding of Cloud Platforms (e.g. Azure / AWS/GCP) and ability to use them for developing, training and testing deep learning models (good to have).
• Preferable Cloudera experience.
• Credit Risk Scorecard development for different lending products such as business loans (LAPs, Working Capital, Merchant Financing etc.), micro-finance, commercial vehicles, commercial equipment financing.
• Adept at complete model lifecycle from defining and designing project, data gathering/pipelining, feature engineering, ML model development & validation, Auto ML, model documentation, deployment to continous monitoring, excellent understanding of overall MLOps - CIC/CD pipeline development
• Experience of data pre-processing and data manipulation using Python or SQL
• Risk & Marketing score (b-score, m-score) model development experience
• Good knowledge of SQL, Big data, HDFS, Cloud, ML model, Spark
• Understanding of Retail, MSME, corporate, commercial banking products excellent understanding of banking feature stores.
• Should have some experience of statistical analysis and modeling techniques (e.g., regression, classification, clustering).
• Experience with machine learning, deep learning frameworks and libraries ( good to have)
• Experience with data visualization tools like Tableau or Power BI.
• Track record of managing data project delivery including ability to meet deadlines, overcome challenges, manage stakeholder expectations, and produce clear deliverables
• Strong problem-solving skills with a keen attention to detail. Ability to think critically and provide data-backed insights.
• Excellent communication skills, both verbal and written.