Senior Data Scientist

We are looking for a Senior Data Scientist with a strong traditional ML/DS background and

hands-on experience in GenAI (LLMs, RAGs, Agentic workflows). The candidate should not be

purely academic or junior; we need someone with practical implementation experience and the

ability to interact confidently with customers. Strong communication and product-facing

exposure are equally important.

My client is seeking a Senior Data Scientist for our Enterprise Products team. In this

role, you will leverage advanced analytical techniques and machine learning methods to derive

actionable insights from complex datasets. Your primary responsibilities will include developing

predictive models, analyzing data to identify trends, and collaborating with cross-functional

teams to implement data-driven solutions that enhance our enterprise product offerings.

Key Responsibilities:

• Develop and implement machine learning algorithms to solve complex business problems.
• Analyze large datasets to generate insights and inform decision‑making processes.
• Collaborate with product managers and engineers to integrate data science solutions
• Communicate findings and recommendations effectively to technical and non‑technical stakeholders.
• Stay current with the latest advancements in data science and machine learning technologies.

Skills and Tools Required:

• Strong proficiency in programming languages such as Python or R.
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit‑learn).
• Solid understanding of statistical analysis techniques and data modeling.
• Proficiency in data visualization tools (e.g., Tableau, Power BI).
• Familiarity with big data technologies (e.g., Hadoop, Spark).
• Ability to work with databases and query large datasets using SQL.
• Strong problem‑solving skills and the ability to think critically.
• Excellent communication and collaboration skills.

Preferred Qualifications:

A master's or Ph.D. in computer science, statistics, mathematics, or a related field.

Experience in the tech industry or with enterprise‑level software products.

Understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud).

About the Role:

As a Senior Data Scientist in Enterprise Products, you will utilize advanced analytical techniques to drive insights from large datasets. Your role will involve building predictive models and enhancing data‑driven decision‑making processes within the organization. You will collaborate with various teams to identify opportunities for leveraging data to optimize products and services.

About the Team:

You will be part of a dynamic team of data scientists, analysts, and product managers dedicated

to creating innovative solutions for enterprise‑level clients. The team thrives on collaboration,

leveraging diverse expertise to tackle complex challenges. A culture of continuous learning and

knowledge sharing is fostered, allowing team members to stay up‑to‑date with the latest

industry trends and technologies.

You are Responsible for:

• Developing and deploying machine learning models to solve business problems.
• Analyzing complex datasets to extract actionable insights that contribute to product development.
• Collaborating with cross‑functional teams to integrate data science solutions into existing products and services.
• Providing mentorship and guidance to junior data scientists and fostering a collaborative

To succeed in this role – you should have the following:

• Strong experience in machine learning algorithms and statistical modeling techniques.
• Proficiency in programming languages such as Python or R, along with data
• Experience with big data technologies like Hadoop, Spark, or similar platforms.
• Excellent analytical skills with the ability to communicate complex findings to non‑technical stakeholders.
• A degree in a quantitative field, such as Computer Science, Statistics, Mathematics, or related disciplines.

Must Haves:

• 5 to 7 years of relevant experience.
• Hands‑on Agentic AI production experience (e.g., LangGraph, LangChain, MCP, retrieval, reranking, and knowledge graphs).
• AWS Bedrock experience (Azure OpenAI or Vertex AI acceptable as alternative
• Strong traditional ML/DS foundation (classification, regression, forecasting, anomaly detection, feature engineering, and model evaluation).
• At least 12 months of continuous, recent hands‑on GenAI/LLM work in production (excluding certification‑only or entry‑level exposure).
• Proven track record of deploying live AI/ML systems into production
• Strong client‑facing and consulting communication skills, with the ability to articulate architectural trade‑offs to non‑technical stakeholders.
• Willingness to attend an in‑person interview at Santa Clara, CA office.

Exclusions & Strict Non-Qualifications

Please do not submit candidates who match any of the following criteria:

• Have less than 12 months of hands‑on GenAI/LLM production experience or possess certification‑only exposure.
• Lack depth in traditional machine learning and data science fundamentals.
• Are unable or unwilling to attend an in‑person interview in Santa Clara, CA.

Nice to Haves:

• Domain experience in the Energy sector (highly preferred).
• Familiarity with Databricks, Snowflake, gradient boosting frameworks (e.g., XGBoost, CatBoost), or LLMOps and evaluation tooling.