Data Scientist

slice

A new bank for a new India

slice's purpose is to make the world better at using money and time, with a major focus on building the best consumer experience for your money. We've all felt how slow, confusing, and complicated banking can be. So, we're reimagining it. We're building every product from scratch to be fast, transparent, and feel good, because we believe that the best products transcend demographics, like how great music touches most of us.

Our cornerstone products and services: slice savings account, slice UPI credit card, slice UPI, and slice business are designed to be simple, rewarding, and completely in your control. At slice, you'll get to build things you'd use yourself and shape the future of banking in India. We tailor our working experience with the belief that the present moment is the only real thing in life. And we have harmony in the present the most when we feel happy and successful together.

We're backed by some of the world's leading investors, including Tiger Global, Insight Partners, Advent International, Blume Ventures, and Gunosy Capital.

About the team

You will work with the team who builds data science solutions for all verticals within slice (Credit Risk, Payments, Product CX, Fraud, AI) to drive the best customer experience. We have classic 0-1 problems galore to solve and want folks who can roll up their sleeves and are up for a challenge. Team plays a critical role in enhancing the accuracy and efficiency of credit underwriting processes through alternative data. The Data Science team ensures optimal risk management, helps minimize default rates, and supports the organization in maintaining a healthy and profitable credit portfolio.

About the role

Data Scientists at slice play a critical role in shaping credit, fraud, and business strategies by building intelligent, scalable, and automation-first solutions. Beyond traditional modeling, the role now extends into leveragingAI/LLMs to automate workflows, enhance productivity, and accelerate decision systems across the organization.

What you will do

• Own end-to-end data science workflows, from data wrangling and feature engineering to model building, evaluation, deployment, and monitoring.
• Build and improve credit underwriting and risk models, leveraging both traditional and alternative data sources.
• Design and deploy AI/LLM-powered solutions to automate decision-making systems (e.g., fraud investigation, reporting, content generation).
• Contribute to automation of fraud and risk workflows, improving decision speed and reducing manual effort.
• Work on model deployment and lifecycle management, ensuring seamless transition from experimentation to production.
• Develop tools/plugins to improve team productivity (e.g., automated reporting, variable builders, idea generators).
• Partner with cross-functional teams (credit, product, marketing, risk) to translate business problems into scalable DS/AI solutions.
• Ensure models align with regulatory standards, business goals, and risk frameworks.
• Monitor model performance post-deployment and continuously iterate for improvements.
• Leverage infrastructure (e.g., GPU environments) to optimize training efficiency and experimentation cycles.

What you will need

• Bachelor's or master's degree in a quantitative discipline (Statistics, Computer Science, Engineering, Economics, etc.).
• 2–5 years of experience in Data Science, Machine Learning, or related fields.
• Strong programming skills in Python, with hands-on experience in libraries like numpy, pandas, scikit-learn, etc.
• Solid understanding of machine learning techniques:
• Supervised: Linear/Logistic Regression, Tree Models, Random Forest, Neural Networks
• Unsupervised: Clustering (k-means), PCA, etc.
• Experience in credit risk, fraud analytics, or marketing analytics is a strong plus.
• Exposure to LLMs / Generative AI use cases (prompting, automation, workflow integration) is highly desirable.
• Understanding feature engineering techniques and trade-offs.
• Experience with model deployment, monitoring, and lifecycle management.
• Strong problem-solving skills with a design-thinking mindset. The ability to build simple, scalable, high-impact solution is important.
• High ownership, strong communication skills, and ability to work in a fast-paced, cross-functional environment.
• Curiosity and ability to experiment with new AI/ML methodologies and tools

Life at slice

Life so good, you'd think we're kidding:

• Competitive salaries. Period.
• An extensive medical insurance that looks out for our employees & their dependents. We'll love you and take care of you, our promise.
• Flexible working hours. Just don't call us at 3AM, we like our sleep schedule.
• Tailored vacation & leave policies so that you enjoy every important moment in your life.
• A reward system that celebrates hard work and milestones throughout the year. Expect a gift coming your way anytime you kill it here.
• Learning and upskilling opportunities. Seriously, not kidding.
• Good food, games, and a cool office to make you feel like home. An environment so good, you'll forget the term colleagues can't be your friends.