{"id":1240134,"url":"https://alion.io/job/exxonmobil-advanced-data-scientist","title":"Advanced Data Scientist","company":{"id":15984,"name":"ExxonMobil","domain":"exxonmobil.com","url":"https://alion.io/company/exxonmobil","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"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":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":28000,"max_usd":58000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":9},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"CI/CD","optional":false},{"name":"Computer Vision","optional":false},{"name":"Git","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"NLP","optional":false},{"name":"NumPy","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"TensorFlow","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Azure","optional":true},{"name":"Databricks","optional":true},{"name":"Reinforcement Learning","optional":true}],"status":"live","first_seen_at":"2026-09-05T07:00:00Z","employer_posted_date":"2026-09-05","last_verified_at":"2026-09-25T19:03:25Z","board_verified":true,"closed_at":null,"days_open":21,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":21},"description":"About us\nAt ExxonMobil, our vision is to lead in energy innovations that advance modern living and a net-zero future. As one of the world’s largest publicly traded energy and chemical companies, we are powered by a unique and diverse workforce fueled by the pride in what we do and what we stand for.\nThe success of our Upstream, Product Solutions and Low Carbon Solutions businesses is the result of the talent, curiosity and drive of our people. They bring solutions every day to optimize our strategy in energy, chemicals, lubricants and lower-emissions technologies.\nWe invite you to bring your ideas to ExxonMobil to help create sustainable solutions that improve quality of life and meet society’s evolving needs. Learn more about our What and our Why and how we canwork together.\nWhat Will You Do\nWork with data scientists, data analysts, computational engineers, machine learning engineers, software developers, or business representatives across our global organization to research, develop, and deliver data science tools, models, or software for solving challenging business problems in the oil and gas industry.\nLead end-to-end delivery of AI/ML solutions: scoping, modeling, evaluation, deployment, and monitoring.\nDevelop GenAI/NLP applications, and/or time-series, computer vision, commercial analytics models. \nBuild production-ready solutions applying MLOps best practices (MLflow, CI/CD, monitoring, data quality).\nApply data science methods, machine learning tools, visualization and/or statistical techniques along with domain knowledge to generate actionable insights and provide optimized recommendations.\nAbout You - Skills and Qualifications\nExpertise in one or more of the following: Time Series Analysis, Computer Vision, Natural Language Processing, Generative AI, Commercial Analytics.\nMaster’s or Ph.D. degree from a recognized university in one of the following disciplines: Data Science, Computer Science, IT, Chemical Engineering, Mechanical, Civil, Materials, Aerospace, Geoscience/Geophysics, Applied Math or related disciplines with a minimum GPA of 7.0.\n5+ years of relevant experience in developing, delivering, and validating production-ready AI/ML solutions.\nIn-depth knowledge and practical experience in statistical analysis techniques (e.g., classification, regression, time-series, Bayesian techniques) and machine learning techniques (e.g., decision trees, ensemble methods, deep learning, neural networks, causal analysis).\nPractical experience in the full machine learning lifecycle from problem formulation, data acquisition, data cleaning to model building and deployment at enterprise level.Proficiency in Python or R, ML frameworks (PyTorch, TensorFlow, scikit-learn) and libraries (NumPy, pandas).\nExperience with software engineering practices, agile methodologies and version control (Git).\nStrong communication and interpersonal skills, with the ability to work collaboratively in a global team environment.\nKey Skills\nApplied Data Science\nStatistical Modeling & Analysis\nMachine Learning & Deep Learning\nGenerative AI, NLP, Computer Vision\nTime Series Analysis & Forecasting\nEnd-to-End ML Project Lifecycle\nPython/R Programming Skills\nSoftware Engineering & Agile Framework\nPreferred Experience\nExcellent problem-solving skill and attention to detail.\nPrior experience with oil & gas, commercial domain, supply chain, production systems, wells or subsurface domain is highly desirable.\nExperience working with Azure Databricks or other data science frameworks.\nExperience with mathematical modeling, physics-based simulators, scientific computing and numerical methods would be an added advantage.\nFunctional Skills\nDeep & Reinforcement Learning\nMachine Learning\nBayesian & Causal Inference\nApplied Software Engineering for Data\nMathematical Framing of Business Problems\nNothing herein is intended to override the corporate separateness of local entities. Working relationships discussed herein do not necessarily represent a reporting connection, but may reflect a functional guidance, stewardship, or service relationship.\nExxon Mobil Corporation has numerous affiliates, many with names that include ExxonMobil, Exxon, Esso and Mobil. For convenience and simplicity, those terms and terms like corporation, company, our, we and its are sometimes used as abbreviated references to specific affiliates or affiliate groups. Abbreviated references describing global or regional operational organizations and global or regional business lines are also sometimes used for convenience and simplicity. Similarly, ExxonMobil has business relationships with thousands of customers, suppliers, governments, and others. For convenience and simplicity, words like venture, joint venture, partnership, co-venturer, and partner are used to indicate business relationships involving common activities and interests, and those words may not indicate precise legal relationships.","description_format":"text","description_chars":4919,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Fossil Fuels","Oil & Gas"],"lifecycle":[{"event":"open","at":"2026-09-25T16:37:22Z"}],"liveness":{"score":69,"band":"ok","label":"Likely open","p_open":1,"p_active":0.772,"p_room":0.9,"age_days":20,"expected_fill_days":31,"reasons":["conf:10","win:mid","comp:brand"],"computed_at":"2026-09-26T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/exxonmobil-advanced-data-scientist","json_url":"https://alion.io/job/exxonmobil-advanced-data-scientist.json","meta":{"generated_at":"2026-09-27T01:50:20Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":1681,"day_limit":5000,"remaining_today":3319,"minute_limit":60,"resets_at":"2026-09-28T00:00:00Z"}}}