Jobgether

Senior Data Scientist – Generative AI

Jobgether United States · $118K–$162K/yr

Internet Marketplace Platforms · 11-50 employees

14 h ago
Remote data-scientist Senior (5-10 yrs) Full-time United States
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About the role

Design, develop, and deploy production-ready LLM applications and multi-step AI workflows to transform unstructured data into business insights. Collaborate with cross-functional teams to transition GenAI prototypes into scalable, reliable solutions while ensuring data governance and security standards.

What they look for

Python Generative AI LLM Natural Language Processing Machine Learning RAG LangChain Databricks Snowflake Prompt Engineering Agentic AI Spark Azure Google Cloud Platform Data Governance MLOps

Requirements

Requires a Bachelor's degree with 5+ years of experience or a Master's degree with 3+ years of experience in a quantitative discipline. Candidates must possess strong Python proficiency and deep expertise in NLP, LLM architectural patterns, and modern cloud data platforms.

Benefits

Medical insurance Dental insurance Vision insurance 401(k) retirement savings plan Paid time off Company holidays Personal holidays Paid parental leave Paid caregiver leave Short-term disability coverage Long-term disability coverage Life insurance Bonus incentive plan

Full description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist – Generative AI based in the United States.

This role offers the opportunity to design and deliver innovative Generative AI applications that transform complex, unstructured data into actionable business insights. You’ll build scalable LLM-powered solutions that improve operational efficiency, inform strategic decisions, and enhance customer experiences. Working across data, product, engineering, and platform teams, you’ll take high-value AI use cases from concept through production. The role combines applied machine learning, NLP, agentic AI, and strong software engineering practices. You’ll work with modern cloud and data platforms while establishing rigorous standards for evaluation, reliability, security, and responsible AI. This is a hands-on opportunity to help shape enterprise-grade GenAI capabilities in a collaborative, impact-focused environment.

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Accountabilities:

  • Design, develop, and deploy production-ready LLM applications focused on conversational intelligence, insight generation, and long-form unstructured data.
  • Build multi-step AI workflows incorporating retrieval, orchestration, routing, tool use, and agentic patterns.
  • Develop robust evaluation frameworks for LLM applications, measuring response quality, reliability, safety, performance, and business value.
  • Apply natural language processing and machine learning techniques to extract meaningful insights from conversations, transcripts, documents, and other text-based data.
  • Work with large-scale structured and unstructured datasets using modern platforms such as Spark, Databricks, and Snowflake.
  • Partner closely with product, engineering, and platform teams to transition GenAI prototypes into scalable, reliable production solutions.
  • Develop clean, maintainable Python code and contribute to engineering best practices including version control, documentation, testing, and code reviews.
  • Design end-to-end GenAI and agentic AI solutions while balancing model capabilities, latency, reliability, cost, and business requirements.
  • Ensure AI solutions meet enterprise standards for data governance, privacy, security, compliance, and responsible AI.
  • Collaborate with technical and non-technical stakeholders to translate complex business challenges into practical AI solutions and communicate results effectively.
  • Explore emerging GenAI approaches, frameworks, and technologies to identify new opportunities for automation, insight generation, and customer impact.

Requirements:

  • Bachelor’s degree with 5+ years of relevant experience, Master’s degree with 3+ years of experience, or PhD-level study in computer science, data science, engineering, or another quantitative discipline.
  • Strong proficiency in Python and modern software development practices for AI and machine learning applications.
  • Deep experience working with natural language data and building text-based products using techniques such as text mining, embeddings, transformers, and modern NLP approaches.
  • Hands-on expertise with LLM prompt engineering and architectural patterns such as retrieval-augmented generation (RAG) and multi-agent systems.
  • Experience developing tool-integrated and agent-based LLM workflows using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or comparable technologies.
  • Experience with cloud and modern data platforms, including Azure, Databricks, Google Cloud Platform, and Snowflake.
  • Demonstrated ability to design, evaluate, deploy, and support AI applications in production or enterprise environments.
  • Strong understanding of LLM behavior, evaluation methodologies, reliability, safety, and the trade-offs involved in deploying GenAI solutions at scale.
  • Experience with data governance, privacy, security, compliance, and responsible AI requirements.
  • Strong communication and collaboration skills, with the ability to work effectively across technical, business, product, engineering, and platform teams.
  • Experience with MLOps, DevOps, or software engineering practices is preferred.
  • A PhD in Computer Science or a related quantitative field is preferred.
  • Experience within healthcare, medical, pharmaceutical, or another highly regulated industry is a plus.
  • Demonstrated experience building end-to-end GenAI or agentic AI solutions for real-world production use cases is highly valued.
  • Experience working with long-context data, including chats, transcripts, and long-form documents, in production environments is preferred.
  • Ability to work within the Eastern or Central U.S. time zones.
  • For remote work, access to a dedicated workspace and reliable internet service with minimum speeds of approximately 25 Mbps download and 10 Mbps upload is required.
  • Ability to travel occasionally for training, meetings, or other business needs.

Benefits:

  • Annual base salary range of $117,600–$161,700, depending on location, skills, experience, education, certifications, and other job-related factors.
  • Eligibility for a bonus incentive plan based on company and/or individual performance.
  • Medical, dental, and vision insurance.
  • 401(k) retirement savings plan.
  • Paid time off, company holidays, and personal holidays.
  • Paid parental and caregiver leave.
  • Short-term and long-term disability coverage.
  • Life insurance.
  • Additional benefits and programs supporting physical, financial, and emotional well-being.
  • Remote work flexibility within eligible U.S. locations and time zones.
  • Opportunities to work on high-impact Generative AI initiatives involving enterprise-scale data, modern AI architectures, and customer-focused applications.
  • A collaborative environment connecting data science, engineering, product, and platform teams.

\nHow Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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