{"id":1579883,"url":"https://alion.io/job/thermo-fisher-scientific-data-analyst-analytics-engineering-ai","title":"Data Analyst – Analytics Engineering & AI","company":{"id":7922,"name":"Thermo Fisher Scientific","domain":"thermofisher.com","url":"https://alion.io/company/thermo-fisher-scientific","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":78,"open_postings":153,"ghost_share":0,"stale_share":0.869,"repost_share":0,"time_to_fill_p50_days":28,"computed_at":"2026-10-21T05:46:15Z"}},"role":"Analytics","role_family":"Analytics","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":9000,"max_usd":21000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":12},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"Embeddings","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Hadoop","optional":false},{"name":"Machine Learning","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"Semantic Search","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"Teradata","optional":false}],"status":"live","first_seen_at":"2026-10-01T12:34:16Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-21T11:06:12Z","board_verified":true,"closed_at":null,"days_open":19,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":19},"description":"Work Schedule\nStandard (Mon-Fri)Environmental Conditions\nOfficeJob Description\nJob Summary\nAt Thermo Fisher Scientific, our mission is to enable our customers to make the world healthier, cleaner, and safer.\nWe are seeking a Data Analyst - Analytics Engineering & AI to support the development of modern enterprise analytics capabilities and help accelerate the evolution of digital analytics toward AI-supported insights.\nReporting to the Senior Manager, Analytics & Insights, the Data Analyst will work at the intersection of business analytics, data visualization, analytics engineering, data modeling, and AI-enabled analytics.\nThis role will partner with business stakeholders, senior analysts, data engineers, architects, and product teams to transform business questions into trusted datasets, analytical models, dashboards, reports, and actionable insights.\nThe Data Analyst will also contribute to the development of an AI-ready analytics foundation by helping organize business metrics, metadata, data relationships, definitions, and analytical datasets so they can be consistently used across dashboards, self-service analytics, conversational analytics, and emerging AI applications.\nThe ideal candidate is analytically curious, technically capable, comfortable working with complex data, and interested in developing skills across analytics engineering, semantic modeling, and AI-enabled analytics.\nMAJOR JOB DUTIES AND RESPONSIBILITIES\nPartner with business stakeholders and senior analytics team members to understand business questions, reporting requirements, KPIs, and analytical needs.\nAnalyze large and complex datasets to identify trends, patterns, opportunities, anomalies, and drivers of business performance.\nDevelop recurring and ad hoc analyses supporting commercial, customer, digital, operational, and strategic initiatives.\nBuild and maintain dashboards, reports, scorecards, and visualizations that provide clear and actionable insights to business stakeholders.\nWrite and maintain SQL queries and data transformations used to create analytical datasets and support reporting and analysis.\nAssist in developing reusable analytical datasets and data models that improve consistency and reduce duplicated reporting logic.\nSupport the development and maintenance of a trusted semantic analytics layer, including business definitions, KPIs, dimensions, measures, hierarchies, and relationships.\nWork with senior analysts and business stakeholders to document and validate metric definitions and ensure consistent interpretation across analytical products.\nPerform data profiling, validation, reconciliation, and quality checks to identify inconsistencies, missing data, or unexpected results.\nInvestigate data-quality and reporting issues and partner with analytics engineering and data engineering teams to identify root causes.\nSupport the creation and maintenance of documentation covering data sources, transformations, metric calculations, business rules, assumptions, and analytical logic.\nAssist with ETL/ELT and analytics engineering activities, including data transformations, testing, validation, and maintenance of curated analytical datasets.\nUse Python or similar analytical technologies for data preparation, automation, exploratory analysis, validation, and analytical workflows as appropriate.\nSupport customer, product, digital, marketing, commercial, and operational analytics initiatives through data exploration and performance measurement.\nAssist with experimentation, segmentation, funnel analysis, customer journey analysis, KPI tracking, forecasting, and other analytical methodologies as needed.\nWork with senior team members to identify opportunities to automate manual reports, repetitive analysis, and data-preparation processes.\nSupport the transition from traditional reporting toward more self-service, proactive, and AI-enabled analytical experiences.\nParticipate in the development and testing of conversational analytics, natural-language querying, AI-generated insights, semantic search, and other emerging analytical capabilities.\nValidate AI-generated analytical outputs by comparing responses against trusted datasets, established metrics, source systems, and documented business rules.\nHelp organize metadata, business definitions, and semantic context so AI-enabled analytics solutions can more accurately interpret enterprise data.\nCollaborate with data engineering, architecture, security, product, and governance teams to ensure analytical solutions follow organizational standards.\nParticipate in peer reviews, testing, documentation, and continuous improvement of analytics products and processes.\nCommunicate analytical findings clearly to both technical and non-technical stakeholders using effective visualizations, summaries, and recommendations.\nContinuously develop knowledge of modern analytics, data engineering, semantic technologies, cloud data platforms, generative AI, and emerging analytical practices.\nQUALIFICATIONS (Education/Training, Experience and Certifications)\nBachelor's degree in Computer Science, Data Science, Engineering, Information Systems, Business Analytics, Statistics, Mathematics, Economics, or a related quantitative discipline.\nEquivalent combination of education and relevant professional experience may be considered.\nAdvanced degree or relevant professional certifications are beneficial but not required.\n2-5 years of experience in data analytics, business intelligence, analytics engineering, data engineering, data science, or a related discipline.\nExperience working with structured datasets and translating business questions into analytical outputs.\nExperience developing dashboards, reports, analyses, or analytical datasets in a business environment.\nExperience working with relational databases, cloud data warehouses, or enterprise analytical platforms.\nExposure to data modeling, dimensional modeling, semantic models, metrics layers, or curated analytical datasets is preferred.\nExperience with cloud-based data platforms such as Snowflake, Teradata, Hadoop, AWS, Azure, Google Cloud Platform, or similar technologies is beneficial.\nExperience with digital analytics technologies such as Google Analytics or Adobe Analytics is beneficial.\nExposure to enterprise systems such as SAP, ERP, CRM, digital commerce, marketing, customer, or operational platforms is preferred.\nExposure to generative AI, conversational analytics, natural-language querying, semantic search, machine learning, or AI-enabled analytics is beneficial\nTECHNICAL SKILLS\nStrong SQL skills, including joins, aggregations, subqueries, common table expressions, window functions, and analytical querying.\nWorking knowledge of Python or another analytical programming language for data manipulation, automation, analysis, or validation.\nExperience with visualization and business intelligence technologies such as Tableau, Power BI, or similar tools.\nUnderstanding of data structures, relational databases, analytical datasets, and basic data modeling concepts.\nFamiliarity with ETL/ELT concepts and modern data-transformation workflows.\nUnderstanding of data-quality principles, including validation, reconciliation, completeness, consistency, and accuracy.\nFamiliarity with version control, documentation, testing, or collaborative software/data development practices is beneficial.\nBasic understanding of cloud data architectures and modern data warehouse technologies.\nInterest in or exposure to generative AI, large language models, semantic search, embeddings, knowledge models, or AI agents is preferred.\nAbility to understand how business definitions, metadata, data relationships, and metric calculations affect analytics and AI-generated insights.\nANALYTICS & AI SEMANTIC ENGINEERING CAPABILITIES\nThe Data Analyst will have the opportunity to develop capabilities beyond traditional reporting and contribute to the semantic and analytical foundation supporting next-generation analytics.\nKey responsibilities may include:\nSupporting the definition and maintenance of reusable business metrics and KPIs.\nHelping document business terminology and map business concepts to enterprise data.\nAssisting in defining relationships between customers, products, channels, transactions, campaigns, digital interactions, and other business entities.\nBuilding analytical datasets that can be reused across dashboards, reports, analyses, and AI-enabled applications.\nHelping identify differences between business terminology and source-system definitions.\nContributing metadata, definitions, descriptions, and contextual information that improve self-service and AI-enabled analytics.\nTesting natural-language questions against analytical datasets and identifying cases where AI-generated responses are inaccurate or ambiguous.\nValidating AI-generated analytical responses against trusted data and established business definitions.\nSupporting data and semantic quality controls that improve accuracy, consistency, explainability, and trust.\nDeveloping an understanding of how governed enterprise data can support AI agents and conversational analytical experiences.\nCORE COMPETENCIES\nStrong analytical and problem-solving skills.\nCuriosity and willingness to investigate unfamiliar data and business problems.\nAbility to translate data into clear observations and business insights.\nStrong attention to detail and commitment to analytical accuracy.\nAbility to communicate findings effectively to technical and non-technical audiences.\nAbility to work collaboratively across analytics, engineering, product, technology, and business teams.\nAbility to manage multiple assignments and priorities in a fast-paced environment.\nWillingness to ask questions, challenge assumptions constructively, and seek deeper understanding of business problems.\nStrong documentation and organizational skills.\nCommitment to continuous learning and development across analytics, data engineering, and AI technologies.","description_format":"text","description_chars":9980,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Continuous learning"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Biotechnology","Health Care","Cell & Gene Therapy"],"lifecycle":[{"event":"open","at":"2026-10-01T12:34:16Z"}],"visa":[],"liveness":{"score":40,"band":"fade","label":"Fading","p_open":1,"p_active":0.529,"p_room":0.75,"age_days":19,"expected_fill_days":28,"reasons":["conf:0","stale_co","velocity","win:late","comp:junior,brand"],"computed_at":"2026-10-21T05:46:15Z"},"pay":null,"html_url":"https://alion.io/job/thermo-fisher-scientific-data-analyst-analytics-engineering-ai","json_url":"https://alion.io/job/thermo-fisher-scientific-data-analyst-analytics-engineering-ai.json","meta":{"generated_at":"2026-10-21T12:05:09Z","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":17161,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-22T00:00:00Z"}},"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":7922},"rest":"https://alion.io/mcp/rest/get_company?id=7922"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fthermo-fisher-scientific-data-analyst-analytics-engineering-ai"},{"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%2Fthermo-fisher-scientific-data-analyst-analytics-engineering-ai"},{"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%2Fthermo-fisher-scientific-data-analyst-analytics-engineering-ai"},{"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/thermo-fisher-scientific-data-analyst-analytics-engineering-ai\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fthermo-fisher-scientific-data-analyst-analytics-engineering-ai"}]}