Easebuzz - Data Scientist

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.