{"id":2840378,"url":"https://alion.io/job/nference-intern-data-scientist","title":"Intern - Data Scientist","company":{"id":34471,"name":"Nference","domain":"nference.com","url":"https://alion.io/company/nference","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"intern","employment_type":"internship","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Embeddings","optional":false},{"name":"Git","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"HIPAA","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-10-19T05:46:57Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-21T10:45:26Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Intern - Data Scientist\nLocation: Bangalore, India\nAbout nference\nnference is an AI-powered technology company transforming biomedical research by leveraging large-scale data, advanced machine learning, and deep scientific expertise. Our mission is to accelerate breakthroughs in healthcare and life sciences by building innovative products that help researchers and clinicians solve complex real-world problems.\nOur People\nAt nference, you'll work alongside software engineers, AI researchers, physicians, scientists, and product leaders who are passionate about solving meaningful, real-world problems.\nWe foster a culture of ownership, curiosity, collaboration, technical excellence, and continuous learning. Our teams are encouraged to ask questions, share ideas, learn from experienced colleagues, and contribute to impactful projects.\nThe Opportunity\nWe're looking for a motivated Data Scientist Intern with a strong foundation in Python, statistics, and data analysis. This internship offers an opportunity to work with complex healthcare data, develop data processing workflows, and explore practical applications of machine learning and large language models (LLMs).\nYou will collaborate with experienced data scientists and engineers to prepare and analyze electronic health record (EHR) data, build data pipelines, validate data quality, and support LLM-assisted information extraction and cohort refinement. This role is suited for someone who enjoys solving data-intensive problems, working with messy real-world datasets, and applying statistical reasoning to derive reliable insights.\nWhat You'll Do\nDevelop data pipelines to fetch, aggregate, clean, and preprocess raw patient data from electronic health records (EHRs).\nApply statistical methods to understand data distributions, normalize variables, handle variations, detect anomalies, and assess data quality and integrity.\nDefine, segment, and statistically validate data cohorts for analysis and research.\nBuild basic batch-processing pipelines and automate data transformation workflows.\nSupport LLM-assisted workflows using prompting, structured outputs, embeddings, and retrieval techniques for information extraction and cohort refinement.\nConduct experiments, analyze results, and evaluate data and inference pipeline performance.\nDebug and optimize data processing and inference workflows.\nUse Git for version control and maintain reproducible data workflows.\nDocument data cleaning rules, cohort definitions, analytical methods, and results to support reproducibility.\nFollow data privacy, security, and compliance requirements when handling healthcare data.\nWhat We're Looking For\nRequired Qualifications\nPursuing or recently completed a Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Economics, or a related quantitative field.\nStrong programming skills in Python, with practical knowledge of Pandas and NumPy for data manipulation and analysis.\nSolid understanding of statistical fundamentals, including data distributions, normalization, hypothesis testing, and anomaly detection.\nStrong analytical skills, with the ability to define, segment, and validate data cohorts using appropriate statistical methods.\nUnderstanding of machine learning and natural language processing (NLP) fundamentals.\nFamiliarity with scikit-learn, SQL for data retrieval, and Git.\nAbility to work with messy, inconsistent, and unstructured datasets with strong attention to detail.\nGood problem-solving, documentation, and communication skills.\nWillingness to learn new tools and apply analytical techniques to real-world healthcare problems.\nPreferred Qualifications\nAcademic or personal projects involving data engineering, statistical data analysis, or cohort building.\nExposure to LLM applications, retrieval-augmented generation (RAG), embeddings, or vector databases.\nFamiliarity with LLM prompting and structured outputs for data extraction or analysis.\nAwareness of healthcare data privacy concepts and regulations, such as HIPAA.\nWhat You'll Gain\nHands-on Experience: Work with real-world healthcare data and practical data science workflows.\nTechnical Learning: Gain exposure to machine learning, statistical analysis, data pipelines, and LLM applications.\nMentorship: Learn from experienced data scientists and engineers.\nMeaningful Impact: Contribute to AI-powered solutions that support biomedical research and healthcare innovation.\nCareer Development: Strengthen your analytical and technical skills in a collaborative, research-driven environment.\nEqual Opportunity Employer\nnference is committed to building a diverse, equitable, and inclusive workplace where everyone has the opportunity to thrive. 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