{"id":2427757,"url":"https://alion.io/job/trinet-senior-data-scientist","title":"Senior Data Scientist","company":{"id":1462,"name":"TriNet","domain":"trinet.com","url":"https://alion.io/company/trinet","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":75,"open_postings":34,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-14T06:34:16Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":43000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":55},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Claude Code","optional":false},{"name":"Context Engineering","optional":false},{"name":"Copilot","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Tool Use","optional":false},{"name":"Copilot Studio","optional":true},{"name":"LangChain","optional":true},{"name":"Langfuse","optional":true},{"name":"LangGraph","optional":true},{"name":"LLMOps","optional":true},{"name":"Semantic Search","optional":true},{"name":"Semantic Search","optional":true},{"name":"Time Series Forecasting","optional":true}],"status":"live","first_seen_at":"2026-10-06T07:18:22Z","employer_posted_date":"2026-10-06","last_verified_at":"2026-10-14T09:10:21Z","board_verified":true,"closed_at":null,"days_open":8,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":8},"description":"TriNet is a leading provider of comprehensive human resources solutions for small to midsize businesses (SMBs). We enhance business productivity by enabling our clients to outsource their HR function to one strategic partner and focus on operating and growing their core businesses. Our full-service HR solutions include payroll processing, human capital consulting, employment law compliance and employee benefits, including health insurance, retirement plans and workers’ compensation insurance.\nTriNet has a nationwide presence and an experienced executive team. Our stock is publicly traded on the NYSE under the ticker symbol TNET. If you are passionate about innovation and making an impact on the large SMB market, join us as we power our clients’ business success with extraordinary HR.\nDo not meet every single requirement? Studies have shown that many potential applicants discourage themselves from applying to jobs unless they meet every single requirement. TriNet always strives to hire the most qualified candidate for a particular role, ensuring we deliver outstanding results for our small and medium-size customers. So if you're excited about this role but your past experience doesn't align perfectly with every single qualification in the job description, nobody’s perfect - and we encourage you to apply. You may just be the right candidate for this or other roles.\nA Brief Overview:\nThis is a high-impact, execution-focused role responsible for building and delivering AI-powered agents and agentic workflows that address critical business challenges. The role combines strong applied data science foundations with hands-on delivery using commonly used technology ecosystems, including Anthropic Claude on AWS Bedrock, Claude Code, Microsoft Copilot, GitHub Copilot and related frameworks and observability tools.\nYou will partner with Data & Analytics leaders and cross-functional teams to design and deliver scalable, secure, and compliant AI solutions in enterprise environments. This role is ideal for someone who excels at translating business needs into clear requirements and delivering high-quality AI agents that operate reliably within real-world workflows.\nKey Responsibilities:\nAgentic AI Solution Design and Delivery\nLead the design, development and testing of single-agent and multi-agent solutions using LLMs, prompt and context engineering, retrieval-augmented generation (RAG), tool use and structured outputs.\nTranslate business problems into agent goals, workflow logic, system interactions, acceptance criteria, exception handling and human-in-the-loop controls.\nIntegrate agents with enterprise platforms, APIs, MCP servers, databases, SaaS applications and governed data sources to enable secure end-to-end workflow execution.\nBuild and optimise retrieval, grounding, memory and orchestration patterns that improve accuracy, traceability and task completion.\nEstablish evaluation and observability practices covering quality, groundedness, safety, latency, cost, failure modes and regression testing.\nProductionise solutions through source control, automated testing, deployment, release validation, monitoring, issue triage and continuous optimisation.\nApplied Data Science and Machine Learning\nFrame business problems as analytical, statistical, machine learning or agentic AI use cases, selecting the simplest effective approach.\nPrepare structured and unstructured data and perform feature engineering, model development, validation and error analysis using reproducible Python and SQL workflows.\nDesign experiments and measurement approaches to demonstrate model performance, incremental value and business impact.\nCollaboration, Governance and Leadership:\nPartner with Product, Engineering, Security, Legal, Compliance and business teams to define priorities, dependencies, controls and acceptance criteria.\nEmbed responsible AI practices, including access controls, privacy protections, guardrails, human oversight, fallback mechanisms and audit-ready logging.\nDrive strong engineering and analytical standards through modular design, code quality, peer review, testing discipline and clear documentation.\nCommunicate implementation choices, analytical findings, limitations, delivery risks and production readiness to technical and non-technical stakeholders.\nProvide technical guidance and contribute reusable patterns, evaluation assets and delivery standards across Data & Analytics.\nRequired Qualifications Education:\nBachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering or a related quantitative field. A master’s degree is preferred.\nMust-Have Experience:\n6+ years of experience in data science, machine learning, applied AI or software engineering, including delivery of production solutions.\nHands-on experience building LLM-powered applications or agents using prompt and context engineering, RAG, tool or function calling, orchestration and structured evaluation.\nExperience implementing multi-step workflows with enterprise integrations, exception handling, state management and human-in-the-loop activities.\nStrong Python and SQL skills, with experience writing maintainable, testable and reusable code.\nExperience integrating applications with APIs, databases, vector stores, cloud services and enterprise data sources.\nExperience operationalising AI or machine learning solutions through Git-based source control, CI/CD, testing, deployment, monitoring and ongoing optimisation.\nWorking knowledge of statistical modelling, machine learning, experimental design and model validation.\nAbility to deliver complex solutions with limited oversight and collaborate effectively across technical and business teams.\nPreferred Experience:\nExperience with Anthropic Claude and AWS Bedrock, including model access, knowledge bases, agents, guardrails and enterprise integrations.\nExperience building enterprise agents with Microsoft Copilot or Copilot Studio and connecting them to Microsoft 365, Power Platform or business applications.\nExperience using Claude Code and GitHub Copilot to accelerate software development while maintaining code quality and engineering controls.\nExperience with LangChain, LangGraph or similar orchestration frameworks, and Langfuse or comparable evaluation and observability tooling.\nExperience with vector databases, semantic search, document processing, multi-agent patterns and adversarial or red-team testing.\nExperience applying predictive modelling, natural language processing, optimisation, time-series forecasting or recommendation methods.\nSkills and Abilities:\nAgentic AI and LLM Engineering: Strong understanding of RAG, tool use, orchestration, memory, structured outputs, context engineering and agent evaluation.\nData Science and Statistics: Strong grounding in data exploration, feature engineering, statistical reasoning, machine learning, experimentation and validation.\nSoftware and Data Engineering: Ability to build production-quality Python and SQL solutions and integrate them with governed enterprise systems.\nLLMOps, MLOps and DevOps: Familiarity with version control, testing, deployment pipelines, observability, monitoring and release management.\nResponsible AI and Security: Ability to design controls for privacy, safety, transparency, data protection, auditability and human oversight.\nProblem Solving, Communication and Ownership: Ability to structure ambiguous problems, make evidence-based trade-offs and lead delivery across functions.\nCertifications:\nRelevant agentic AI, generative AI, AWS, data science, machine learning, MLOps or responsible AI certifications are advantageous but not required.\nTravelRequirements:\nMinimal travel required.\nWork Environment\nWork in a clean, pleasant, and comfortable office work setting. The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable persons with disabilities to perform the essential functions.\nThis position is 100% in office.\nPlease Note: TriNet reserves the right to change or modify job duties and assignments at any time. The above job description is not all encompassing. Position functions and qualifications may vary depending on business necessity.\nTriNet is an Equal Opportunity Employer and does not discriminate against applicants based on race, religion, color, disability, medical condition, legally protected genetic information, national origin, gender, sexual orientation, marital status, gender identity or expression, sex (including pregnancy, childbirth or related medical conditions), age, veteran status or other legally protected characteristics. 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