Data Scientist - Credit

About the Role

As a Data Scientist at Care.Fi, you will leverage your expertise in programming, quantitative analysis,

and machine learning to design, develop and maintain statistical risk models and decision-support

analytics. This role is pivotal in driving innovation, automation and process improvement across our

operations while fostering cross-functional collaboration and delivering impactful data-driven

solutions. You will also work closely with stakeholders to ensure models are compliant, effective, and

aligned with the companys objectives.

Key Responsibilities

• Model Development: Build and deploy machine learning models to predict credit risk and other

essential business metrics, ensuring accurate and timely implementation in collaboration with

stakeholders.

• Data Processing: Conduct statistical analysis, feature engineering, dimensionality reduction, and

evaluation of new data sources to enhance model accuracy.

• Machine Learning Techniques: Apply regression, classification, clustering, tree-basedCare.fi Technological solutions Private limited CIN – U72900KA2021PTC153099

Head Office - 802 C 802-A, IRIS Tech Park, Tower A, Badshahpur, Sohna road Hwy sector 48, Gurugram, Haryana -122018

www.carefi.in

algorithms, support vector machines, and other ML techniques to solve complex business

problems.

• Model Optimization: Continuously improve existing methodologies by developing new data

sources, testing model enhancements, and fine-tuning parameters for optimal performance.

• Stakeholder Collaboration: Provide guidance to business units on model use, impact, and

implementation, and ensure alignment with operational needs.

• Governance and Compliance: Partner with model governance teams to develop metrics and

methods for monitoring model performance and compliance with risk standards.

• Systems Understanding: Gain a deep understanding of the systems and business processes that

generate and populate data for analysis.

• Automation: Drive scalability and efficiency by automating workflows and collaborating with

cross-functional teams.

Required Skills and Qualifications

• Educational Background: Bachelor’s or master’s degree in a quantitative field such as

Engineering, Statistics, Computer Science, Mathematics or Econometrics.

• Experience: 2-5 years as a Data Scientist, preferably in the banking or financial services sector.
• Programming Skills: Proficiency in Python, PySpark, SAS, SQL, or similar tools for data analysis

and modeling.

• ML Expertise: Hands-on experience with machine learning models such as XGBoost, LightGBM,

Random Forest, and SVMs, as well as techniques like multivariate analysis and clustering.

• Data Processing: Strong skills in statistical analysis, variable selection, dimensionality reduction,

and feature engineering.

• Production Implementation: Experience collaborating with technology teams to implement

models and algorithms in production environments.

• Communication Skills: Ability to clearly and effectively communicate complex concepts to

stakeholders at all organizational levels.

• Collaboration: Highly motivated and collaborative team player with excellent interpersonal

skills.