{"id":1606486,"url":"https://alion.io/job/innodata-research-data-scientist","title":"Research Data Scientist","company":{"id":48089,"name":"Innodata","domain":"innodata.com","url":"https://alion.io/company/innodata","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":100,"open_postings":8,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":59,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":160000,"max":185000,"currency":"USD","period":"year","gross":null,"usd_annual":185000},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"DPO","optional":false},{"name":"Embeddings","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Hallucination","optional":false},{"name":"Hypothesis","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"NLP","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"RLHF","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SFT","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-09-12T21:07:07Z","employer_posted_date":"2026-09-24","last_verified_at":"2026-10-17T05:20:47Z","board_verified":true,"closed_at":null,"days_open":34,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":34},"description":"Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.\nScope of the Role: \nWe are looking for a highly skilled Research Data Scientist - GenAI/LLM to join our AI/LLM Delivery Unit and work on research-driven AI/ML initiatives involving Generative AI, Large Language Models (LLMs), NLP, multimodal AI, model evaluation, and AI data.\nThe role combines strong research and analytical capabilities with hands-on AI/ML expertise, requiring the candidate to design experiments, develop evaluation methodologies, analyze complex datasets, build research prototypes, and translate research findings into practical AI/ML solutions.\nThe ideal candidate will have a strong research orientation, excellent statistical and analytical skills, and the ability to work collaboratively with researchers, data scientists, AI/ML engineers, domain experts, and client-facing teams.\nWhat You’ll Own:\nAI/ML & Generative AI Research:\nConduct independent and collaborative research in Generative AI, LLMs, NLP, multimodal AI, machine learning, model evaluation, and AI data.\nFormulate research questions and translate complex AI/ML problems into structured research methodologies and experiments.\nDesign, execute, and analyze experiments to evaluate and improve AI/ML models and solutions.\nBuild analytical models, prototypes, and research pipelines using Python and relevant ML frameworks.\nStay current with emerging research, methodologies, papers, and developments in GenAI, LLMs, NLP, multimodal models, and AI evaluation.\nLLM & Model Evaluation:\nDevelop and implement LLM evaluation frameworks, benchmarks, datasets, and evaluation criteria.\nEvaluate models for accuracy, robustness, bias, hallucination, reasoning, relevance, response quality, and other performance dimensions.\nConduct model benchmarking, error analysis, comparative analysis, and performance evaluation.\nWork on areas such as RAG, SFT, RLHF/DPO, prompt engineering, fine-tuning, embeddings, and LLM optimization, as applicable.\nIdentify model and data gaps and recommend improvements to enhance model performance and reliability.\nData Science & Statistical Research:\nCollect, clean, analyze, and interpret large and complex structured and unstructured datasets.\nPerform EDA, statistical analysis, hypothesis testing, significance testing, correlation analysis, sampling, and error analysis.\nDevelop data-driven insights and identify patterns, trends, and relationships relevant to AI/ML research.\nApply appropriate statistical and quantitative methodologies to validate research findings\nAI Data & Dataset Development:\nDevelop and evaluate datasets, sampling methodologies, taxonomies, annotation frameworks, data quality frameworks, and evaluation criteria for AI/ML models.\nAnalyze data quality and identify issues affecting model performance.\nCollaborate with annotation, data engineering, and AI/ML teams to improve AI training and evaluation data.\nTranslate data and research findings into actionable recommendations for improving AI system\nResearch & Innovation:\nContribute to research papers, technical reports, whitepapers, patents, benchmarks, internal publications, and other research outputs, where applicable.\nIdentify opportunities to apply emerging research and technologies to real-world AI and data challenges.\nExplore new methodologies, models, datasets, and evaluation approaches to improve AI capabilities.\nContribute to capability building and innovation within the AI/LLM practice\nCollaboration & Stakeholder Engagement:\nWork closely with researchers, data scientists, AI/ML engineers, data/annotation teams, domain experts, and delivery teams.\nPresent research findings, analytical insights, and technical recommendations to senior technical stakeholders.\nTranslate complex research and technical concepts into clear, actionable recommendations.\nWhere required, participate in client-facing technical discussions and presentations and help translate business requirements into AI/ML solutions.\nYou’ll Thrive in This Role If You Have:\nMaster’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, Mathematics, Computational Science, or a related discipline.\nBachelor’s/Master’s degree from IITs, NITs, or other premier engineering/research institutions is strongly preferred.\n4-7 years of hands-on research experience in AI/ML, Data Science, NLP, Generative AI, LLMs, or related areas.\nStrong demonstrated research experience with the ability to independently formulate research questions, design experiments, analyze results, and communicate findings.\nDemonstrated research track record through research publications, patents, conference presentations, open-source contributions, or significant AI/ML research projects.\nCandidates with publications in reputed conferences/journals and a strong academic/research profile will be preferred\nStrong proficiency in Python and SQL.\nStrong hands-on experience with NumPy, Pandas, Scikit-learn, and preferably PyTorch/TensorFlow.\nStrong understanding of:Machine learning algorithms\nStatistics and experimentation\nData analysis and feature engineering\nModel evaluation and performance metrics\nHypothesis testing and statistical inference\n\nHands-on exposure to LLMs, NLP, Generative AI, and multimodal AI.\nExperience with one or more of RAG, LLM evaluation, prompt engineering, fine-tuning, SFT, RLHF/DPO, embeddings, or model benchmarking.\nExperience working with large-scale structured and unstructured datasets.\nFamiliarity with Git and cloud platforms such as AWS, Azure, or GCP is desirable.\nThe expected salary range for this position is $160,000 - $185,000 p/year, based on experience, skills, and qualifications.\nPlease be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. \nIf you believe you’ve been targeted by a recruitment scam, please report it to Innodata at  and consider reporting it to the FTC at ReportFraud.ftc.gov.","description_format":"text","description_chars":6776,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Data Entry & Processing","AI Training Data & Annotation"],"lifecycle":[{"event":"open","at":"2026-10-01T19:52:38Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 2","filings_12m":2,"filings_prev_12m":2,"green_card_filings_12m":0,"median_offered_wage_usd":150000,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)"],"filings_for_role_12m":0}],"liveness":{"score":73,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.809,"p_room":0.9,"age_days":34,"expected_fill_days":59,"reasons":["conf:0","velocity","win:mid"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":185000,"is_top_pay":true},"html_url":"https://alion.io/job/innodata-research-data-scientist","json_url":"https://alion.io/job/innodata-research-data-scientist.json","meta":{"generated_at":"2026-10-17T08:02:01Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":10845,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":48089},"rest":"https://alion.io/mcp/rest/get_company?id=48089"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Finnodata-research-data-scientist"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Finnodata-research-data-scientist"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Finnodata-research-data-scientist"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/innodata-research-data-scientist\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Finnodata-research-data-scientist"}]}