Senior Data Scientist – Technical AI Solutions

Job Description

REQUIREMENTS

• 5+ years of experience in data science, AI/ML development, or technical consulting.
• Proven track record of delivering production-grade AI/ML solutions end-to-end.
• Strong Python programming skills with solid software engineering practices — testing, code quality, and version control.
• Practical experience building GenAI/LLM applications using frameworks like LangChain, LangGraph, or equivalent.
• Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and containerization (Docker).
• Solid understanding of ML/AI fundamentals including how LLMs work, transformer architectures, and when to apply different approaches.
• Working knowledge of SQL and data pipeline concepts.
• Strong communicator — able to explain complex technical concepts clearly to non-technical audiences.

Preferred

• Experience with data orchestration tools (Airflow, Vertex AI Pipelines) and transformation frameworks (DBT).
• Familiarity with ML algorithms (GBM, GLM) and experimentation frameworks including A/B testing.
• Background in consulting or client-facing delivery environments.
• Experience mentoring or coaching junior technical team members.
• Contributions to open source projects or technical communities.

RESPONSIBILITIES

• Design and build production-grade GenAI and LLM applications using Python and modern AI frameworks (e.g. LangChain, LangGraph).
• Architect and implement AI solutions on major cloud platforms (AWS, Azure, or GCP) using containerization and cloud-native practices.
• Make informed technical decisions on AI approaches — knowing when to use classical ML, LLM prompts, workflows, or agents.
• Design evaluation frameworks and observability metrics to ensure solution quality and performance.
• Develop APIs and build data pipelines using SQL, DBT, and orchestration tools.
• Collaborate with clients and domain experts to understand problems, validate approaches, and translate technical concepts for non-technical stakeholders.
• Conduct code reviews, mentor junior team members, and contribute to team technical standards.
• Support business development through technical scoping, solution design, and proposal contributions.
• Identify and communicate technical risks and trade-offs clearly and proactively.

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