Data Scientist - 2

About Navi 

Navi is one of the fastest-growing financial services companies in India providing Personal & Home Loans, UPI, Insurance, Mutual Funds, and Gold. Navi's mission is to deliver digital-first financial products that are simple, accessible, and affordable. Drawing on our in-house AI/ML capabilities, technology, and product expertise, Navi is dedicated to building delightful customer experiences. Navi, our  mission is to build financial services that are simple, accessible and affordable. 

Founders: Sachin Bansal & Ankit Agarwal 

Know what makes you a “Navi_ite” : 

1.Perseverance, Passion and Commitment 
• Passionate about Navi’s mission and vision 

• Demonstrates dedication, perseverance and high ownership 

• Goes above and beyond by taking on additional responsibilities 

2.Obsession with high quality results 
• Consistently creates value for the customers and stakeholders through high quality outcomes 

• Ensuring excellence in all aspects of work 
• Efficiently manages time, prioritizes tasks, and achieves higher standards 

Data Science @Navi: 

At Navi, our Data Science team is the powerhouse behind scalable and efficient solutions that span across a broad spectrum of fintech sectors—be it lending, insurance, investments, or UPI. We're not just a team; we're the architects of the future of fintech.

• We're not just keeping up with innovation; we're setting the pace. Our team is constantly pushing the boundaries, introducing groundbreaking methods that amplify business growth, enhance customer experiences, and streamline operational processes.
• Our work isn't confined to a single domain. We tackle a diverse set of problem statements, from computer vision and tabular data to natural language processing, speech recognition, and even Generative AI. Each day brings a new challenge and a new opportunity for breakthroughs.
• When you join us, you're not just taking a job; you're becoming a part of a movement. A movement that's making a tangible difference in the fintech landscape, one innovative solution at a time.

Ready for a transformative career journey? Join us at Navi and be a part of a team that's shaping the future of fintech.

What you gain by working with the Data Science team at Navi:

Join the Navi Data Science team for:

Own Your Journey from Start to Finish : Take pride in having full-cycle ownership of your projects. You won't just be a cog in the machine; you'll be the architect, designer, and implementer of cutting-edge Data Science solutions that drive our business forward.

• Immerse Yourself in a Data Wonderland : Welcome to a playground where data is abundant and limitations are few. Our high-growth, agile environment offers a treasure trove of data, giving you the freedom to experiment, innovate, and make data-driven decisions that matter.
• Be Part of a Synergistic Dream Team : Collaborate with a diverse group of high-performing professionals who are as passionate about data science as you are. Our culture fosters continuous learning and upskilling, setting you up for ongoing success and career growth.
• Make a Tangible Impact : Your work won't just sit on a shelf; it will make waves. By closely collaborating with stakeholders across departments, you'll have the opportunity to design and develop data science solutions that not only solve complex problems but also make a meaningful impact on our company and the fintech industry at large

What we are looking for:

Bachelor's or Master's in Engineering or equivalent.

2+ years of Data Science/Machine Learning experience.

Strong knowledge in statistics, tree-based techniques (e.g., Random Forests, XGBoost), machine learning (e.g., MLP, SVM), inference, hypothesis testing, simulations, and optimizations.Bonus: Experience with deep learning techniques.

Strong Python programming skills and experience in building Data Pipelines in PySpark, along with feature engineering.

Proficiency in pandas, scikit-learn, Scala, SQL, and familiarity with TensorFlow/PyTorch.

Understanding of DevOps/MLOps, including creating Docker containers and deploying to production (using platforms like Databricks or Kubernetes).