Data Scientist L3

About CoffeeBeans Consulting

CoffeeBeans is a fast-growing software consulting firm known for solving complex business problems using cutting-edge engineering, AI, and data science. Our teams deliver end-to-end solutions across ML and GenAI, with a strong focus on building production-grade systems that drive measurable value for clients in fintech, retail, healthcare, logistics, and beyond.

Role Overview

As a L3 Data Scientist, you will lead the design, development, and deployment of advanced machine learning and GenAI applications. You will be responsible for end-to-end ownership of model development, fine-tuning LLMs, and building intelligent systems that integrate seamlessly into client products. This role combines deep technical expertise, product thinking, and the ability to mentor and influence others.

This is a senior individual contributor role, ideal for professionals who thrive on solving ambiguous, high-impact problems using a blend of classical ML and cutting-edge LLM technologies.

Key Responsibilities

ML & Data Science Leadership

• Lead the development of robust machine learning solutions across supervised, unsupervised, and time-series problems.

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  Architect and own pipelines for feature engineering, training, evaluation, and monitoring of models.

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  Apply advanced experimentation techniques, error analysis, and iterative improvements to meet business KPIs.

LLM & GenAI System Development

• Design and implement GenAI-powered solutions such as copilots, document processors, summarization agents, and intelligent assistants.

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  Build advanced workflows using prompt engineering, RAG pipelines, context management, and hybrid model chaining.
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  Lead LLM fine-tuning efforts using instruction tuning, parameter-efficient methods (LoRA, QLoRA, PEFT), or full-model fine-tuning for domain-specific use cases.

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  Evaluate trade-offs across LLM providers (open-source vs API-based) and optimize for performance, cost, and latency.

Collaboration & Impact

• Partner with engineering, product, and business teams to shape technical direction and translate insights into deployed solutions.

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  Contribute to pre-sales activities, PoC development, and client workshops as a technical SME.

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  Drive technical quality, review deliverables, and ensure adherence to best practices across the data science lifecycle.

Mentorship & Technical Leadership

• Mentor junior and mid-level data scientists on modeling approaches, GenAI architecture, and clean experimentation workflows.

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  Lead internal sessions on advancements in ML/LLM ecosystems and guide capability development within the team.

Required Skills & Qualifications

• 6–9 years of hands-on experience in data science, machine learning, or AI product development.

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  Strong Python programming skills with expertise in libraries like pandas, NumPy, scikit-learn, XGBoost/LightGBM.
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  Proven track record of shipping ML models to production (batch or real-time) in business-critical applications.
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  Hands-on experience working with LLMs (OpenAI, Mistral, Claude, LLaMA) and frameworks like LangChain or LlamaIndex.
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  Direct experience in fine-tuning LLMs using Hugging Face Transformers, PEFT, or custom pipelines.
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  Strong understanding of prompt engineering, embeddings, similarity search, and vector databases (e.g., FAISS, Pinecone).

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  Experience with Docker, Git, and cloud platforms (AWS, GCP, or Azure).

Good-to-Have

• Exposure to ML/GenAI platform design and MLOps tools (e.g., MLflow, SageMaker, Weights & Biases).

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  Experience with evaluation and safety frameworks for GenAI applications.

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  Contributions to open-source projects or demonstrable personal projects in ML/LLMs.

What You’ll Love at CoffeeBeans

• Solve real-world problems with ML and GenAI, not just toy models or prototypes.

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  Collaborate with talented engineers, designers, and product thinkers in a flat, high-ownership environment.
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  Work across industries and domains while experimenting with the latest in LLMs and AI tooling.

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  Shape the future of AI development within a fast-growing, impact-focused team.