Job Summary
We are seeking a passionate and detail-oriented Data Scientist to join our team with strong expertise in statistical modeling, machine learning, and data-driven problem-solving. Skilled in transforming complex datasets into actionable insights that drive product, business, and operational decisions. Proficient in Python, SQL, predictive modeling, and data visualization. Adept at building end-to-end ML pipelines and communicating analytical findings to technical and non-technical stakeholders.
Key Responsibilities:
• Develop, deploy, and fine-tune LLMs (Large Language Models) and work on cutting-edge GenAI applications.
• Develop and optimize RAG (Retrieval-Augmented Generation) pipelines.
• Apply traditional machine learning techniques to develop regression and classificationmodels for scoring engines and decision support systems.
• Design, execute, and iterate on rapid Proof-of-Concepts (POCs) for new features andtechnologies.
• Work extensively with Python and SQL for data analysis, manipulation, and modeldevelopment.
• Leverage AWS ecosystem for scalable model training and deployment (BedRock,Sagemaker, EC2, Lambda etc).
• Handle Natural Language Processing (NLP) tasks like entity recognition, sentiment analysis, and text generation.
• Collaborate with cross-functional teams to integrate ML solutions into fintech products.
• Stay updated with the latest advancements in AI/ML and proactively propose new ideas and solutions.
Required Skills:
• Exposure to building Agentic RAG, Graph RAG pipelines, and tuning it.
• Good exposure to a broad range of machine learning algorithms and a solid
understanding of the foundations as well.
• Excellent understanding of ML lifecycle: training, deploying, and monitoring ML models.
• Proficiency in frameworks like Tensorflow, PyTorch, Scikit-learn, Langchain, Llamaindex etc.
• Exposure to traditional algorithms such as Linear & Logistic Regression, Random Forest, XGBoost, Naive Bayes, SVM, ARIMA, SARIMAX.
• Good understanding of NLP, LLMS, VLM (Llama, Anthropic).
• Ability to write and debug complex SQL queries.
• High level of comfort in the AWS ecosystem (EC2, Lambda, Bedrock, Cloudwatch),
• Strong problem-solving and analytical skills with an aptitude to learn and adapt in a fast- paced environment.
• Demonstrated ability to execute rapid POCs and iterate efficiently.
• Prior experience in the fintech domain is a plus.
• Good to have: Docker, Flask, MLFLOW, Airflow, K8s
Eligibility & Qualifications
• Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or arelated quantitative discipline.
• A master’s degree is a plus.
• 1 - 5 Years (Junior & Seniors).
Why Join Us:
• Opportunity to work on impactful data projects in the fintech domain.
• Collaborative and growth-oriented work culture.
• Exposure to cutting-edge tools and technologies in data analytics and automation.
