Principal Data Scientist

You can become a part of

… a truly aspirational brand, one of India’s fastest growing fintech companies that offers a range of financial services & products for merchants, kirana store owners and end consumer. Valued at over $2.8 Bn within a short span of 3+ years, we focus on empowering small business owners and retailers with all things business ranging from QR & PoS payments to easy loans to high-yield investment products which in turn enables them to grow and transform. We understand that business and culture are two sides of the same coin. So, alongside business, we are equally focused on building a culture where employees succeed unconditionally. We are focusing on building a strong culture.

We believe we are in an ever-evolving space with immense opportunity to build for Bharat! Our people will enable this journey with their ideas, innovations and capabilities. We value diversity, where we encourage different points of view, ways of thinking, new capabilities to strengthen and improve the digital strategy for our customers. And that is not all, we have a lot of fun while we explore new ideas, solve real problems, collaborate, connect — and we do it all together.

Connect with us over social media, coffee or call. We promise to excite you with an opportunity that will “change the game”!

In this role, you have the opportunity to

Are you a visionary AI leader ready to shape the future of fintech? BharatPe is seeking an expert Principal Data Scientist specializing in Generative AI and Deep Learning to drive transformative AI solutions. In this pivotal role, you will champion the development and deployment of advanced AI technologies, with a strong emphasis on Generative AI and Deep Learning, to conquer complex challenges within the fintech domain. You will spearhead impactful machine learning and AI initiatives, collaborating closely with cross-functional teams to embed AI deeply into our business strategy and accelerate growth.

Responsibilities will include

• Vision and Execution: Define and lead the execution of groundbreaking AI and deep learning projects that directly address critical business imperatives within the fintech sector.
• Advanced AI Application: Architect and deploy solutions leveraging state-of-the-art Generative AI models, advanced deep learning methodologies, and robust MLOps principles to solve real-world business problems.
• Strategic Collaboration: Partner strategically with engineering, product, and business leadership to forge AI strategies and seamlessly integrate intelligent solutions across our platform.
• Scalable AI Solutions: Architect and deploy scalable AI models that deliver tangible impact across payments, lending, merchant onboarding, KYC processes, and merchant services.
• Innovation Leadership: Stay at the cutting edge of AI advancements, proactively championing the adoption of novel technologies and driving innovation throughout the company.
• Strategic Contribution: Play a key role in shaping the strategic roadmap by identifying and advocating for high-impact opportunities where AI can generate significant business value.
• Team Leadership and Influence: Inspire and guide teams with strong leadership, demonstrating decisive decision-making, critical thinking, and a strategic mindset to overcome complex challenges.
• Exceptional Communication: Articulate intricate technical concepts with clarity and impact to diverse audiences, adapting your communication style to effectively convey the power of AI and aligning with evolving business needs and the dynamic data science landscape.

To succeed in the role;

Qualifications

Master's Degree in a quantitative discipline (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related field)

7-10 years of progressive experience in AI/ML, including at least 4-5 years of hands-on expertise in applying Generative AI, Deep Learning, and MLOps in production environments.

Skills, experiences & behaviors

• Deep AI Expertise: Mastery in Generative AI, deep learning, and Natural Language Processing (NLP), including LLMs, BERT, and RAG-based systems, coupled with a strong understanding of deep learning architectures (e.g., CNNs, RNNs, LSTMs) and traditional machine learning algorithms (Classification, Regression, unsupervised methods, etc.).
• Generative AI for unstructured data: Proven ability to work with large-scale unstructured data, developing and deploying generative AI solutions for text generation, summarization, conversational AI, and code generation.
• Production-Ready Systems: Hands-on expertise in FastAPI, Git, Docker, and cloud-based deployment workflows for building, scaling, and maintaining robust, production-grade ML systems.
• AI Framework Proficiency: Extensive hands-on experience with Python and leading deep learning frameworks such as TensorFlow, PyTorch, Hugging Face, and LangChain to build production-grade AI applications.
• Coding Skills: Fluency in Python, SQL, and PySpark, with a strong track record of developing and deploying production-ready ML pipelines.
• Cloud Deployment Expertise: Demonstrated experience in deploying and managing AI/ML models in major cloud environments (AWS, GCP).
• MLOps Expertise: Strong proficiency in MLOps principles and practices for scaling and deployment, with a proven ability to collaborate effectively with MLOps and engineering teams to deploy and maintain scalable ML solutions for both real-time and batch inferences.
• Data-Driven Impact: Ability to extract actionable insights from data and leverage AI/ML techniques to drive automated resiliency, elevate customer experiences, and optimize revenue generation.

• Exceptional Communication: Outstanding communication skills with the ability to clearly and persuasively explain complex technical solutions to both technical and non-technical stakeholders.

• Business Problem Solving: Proven experience in applying AI/ML to solve complex, real-world business challenges in areas such as growth modeling, fraud detection, payments processing, and customer segmentation.

Good to Have:

• Fintech Acumen: Prior experience within the BFSI industry, particularly in fintech, with specific knowledge of credit risk and fraud detection.
• Business Integration: Hands-on experience with setting up robust monitoring systems, conducting A/B testing for performance validation, and supporting go-to-market (GTM) strategies to ensure successful adoption of AI solutions.