About CoffeeBeans Consulting

CoffeeBeans is a tech-driven software consulting company that helps businesses solve complex problems using modern data, AI, and engineering solutions. We blend deep technical expertise with a product mindset to build scalable, intelligent, and high-impact solutions across industries. Our data science team works on end-to-end delivery—from exploration and modeling to GenAI application development and deployment.

Role Overview

As an L2 Data Scientist, you will play a hands-on role in delivering production-grade ML and GenAI-powered applications. You are expected to independently take ownership of data science components within client projects, contribute to solutioning and design, and mentor junior team members. You will work across a range of use cases such as personalization, fraud detection, intelligent automation, RAG pipelines, and LLM-based assistants.

This role is ideal for someone who has proven experience in both traditional ML and an emerging understanding of LLMs and generative AI applications.

Key Responsibilities

ML & Data Science

Own and deliver ML model development, tuning, and evaluation for client-facing projects.

Contribute to experimentation frameworks and model reproducibility best practices.

GenAI & LLM Applications

Design and prototype GenAI solutions using LLMs (e.g., OpenAI, Claude, Mistral, Llama).

Contribute to benchmarking, safety, and cost-performance trade-offs in LLM app development.

Product & Engineering Collaboration

Collaborate with engineering teams to take models from experimentation to deployment (batch/real-time).

Contribute to technical documentation, explainability reports, and client presentations.

Team & Growth

Mentor junior data scientists and review code/model design.

Participate in discovery and solutioning phases with clients alongside tech leads and PMs.

Required Skills & Qualifications

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Statistics, or a related field.
4.5 - 6 years of hands-on experience in applied data science, including both ML model development and GenAI-based solutioning.

Experience working with REST APIs, Git, and cloud environments (AWS/GCP).

Good-to-Have Skills

Experience with deploying models via FastAPI, Docker, or serverless platforms.

Experience with embeddings, vector databases, and similarity search.

What You Can Expect at CoffeeBeans

Work on real-world AI/ML problems across verticals.

Opportunities to lead, mentor, and influence tech direction.