{"id":4282560,"url":"https://alion.io/job/vitol-com-senior-data-scientist-applied-ml","title":"Senior Data Scientist, Applied ML","company":{"id":691744,"name":"Vitol.com","domain":"vitol.com","url":"https://alion.io/company/vitol","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"A","score":90,"open_postings":5,"ghost_share":0,"stale_share":0.4,"repost_share":0,"time_to_fill_p50_days":50,"computed_at":"2026-11-12T10:38:37Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Houston, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Hugging Face","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Time Series","optional":false},{"name":"Agentic Workflows","optional":true},{"name":"AI Agents","optional":true},{"name":"LLM Evaluation","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"Sentiment Analysis","optional":true}],"status":"live","first_seen_at":"2026-11-13T18:21:41Z","employer_posted_date":"2026-11-13","last_verified_at":"2026-11-13T20:51:37Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Vitol is a leader in energy and commodities. Vitol produces, manages and delivers energy and commodities to consumers and industry worldwide. In addition to its primary business of trading, Vitol is invested in infrastructure globally, with $10+billion invested in long-term assets.\nVitol’s customers include national oil companies, multinationals, leading industrial companies and utilities. Founded in Rotterdam in 1966, today Vitol serves its customers from more than 40 offices worldwide. Revenues in 2025 were $343bn.\nOur people are our business. Talent is precious to us and we create an environment in which individuals can reach their full potential, unhindered by hierarchy. Our team comprises more than 65+ nationalities and we are committed to developing and sustaining a diverse work force.\nLearn more about us here. This role is located in Houston, TX onsite 5x a week\nVitol’s Applied ML team in Houston works directly with the trading desks to find commercial value through data and applied data science . Projects start with a trader’s or analyst’s question, not with a model.\nYou will work alongside traders and analysts from the first conversation through to production and beyond. You frame the problem with them, review results with them as the work progresses, and stay with the tool after it ships.\nYou own both the science and its path to production. The work is fast and phased, and it is judged on one thing: whether the desk uses it to make better decisions.\nWhat You Will Do\nWork side by side with traders and analysts to turn market questions into scoped projects, each with a clear commercial hypothesis and a defined go/no-go point.\nReview progress with the desk throughout each project, not just at handoff. Show intermediate results early, test them against the desk’s market knowledge, and change course when the signal or the priority shifts.\nBuild LLM, NLP and multimodal pipelines that extract structured signals from unstructured sources such as outage reports, news, filings, and web content.\nDesign and run quick experiments to test feasibility across modelling approaches, and stop weak ideas early.\nBuild models that predict outage impacts, classify disruption patterns, and detect anomalies and regime changes in fundamental data.\nTake the models that prove out into production. That means packaged, tested, deployed through CI/CD, with monitoring and drift detection built in from day one.\nDeliver insights where traders already work: Teams, alerts, and the Vision Excel and Python tooling. Standalone dashboards are not the default.\nSource data through the Vision platform. When you need a new source, work with the Vision team rather than building side pipelines, and follow the existing web-scraping architecture.\nEvaluate commercial AI platforms and tools against real desk problems, and give a clear recommendation.\nExplain results, uncertainty, and limits in plain terms to traders, analysts, and senior stakeholders.\nApplied experience: 5+ years applying machine learning and NLP to messy, real-world data, including models you took to production and supported after launch.\nDesk-facing track record: You have worked directly with commercial users in trading, finance, or a similar fast-paced setting, and you can point to decisions your work changed.\nQuantitative foundation: Master’s or PhD in statistics, mathematics, physics, engineering, or equivalent depth gained in industry. Strong statistics and experimental design.\nLLMs and NLP: Hands-on experience building extraction and classification pipelines with LLMs, covering evaluation, prompt and retrieval design, and cost and latency trade-offs.\nPython and ML stack: Python with scikit-learn, PyTorch, and HuggingFace. You write production-quality code that others can review and maintain.\nProduction engineering: Docker, AWS, CI/CD, and MLOps practice, including model versioning, monitoring, and retraining.\nTime series and signals: Experience with anomaly detection and with combining signals across multiple time-series and text sources.\nCommunication: You can explain what a model means for a trade in two sentences, and you are comfortable being challenged by people who know the market better than you do.\nNice to have: Knowledge of energy or commodities markets, graph modelling, sentiment analysis, or agentic workflows and MCP.\nWhat Success Looks Like in Year One\nTraders and analysts on at least two desks bring problems to you directly.\nAt least two proof-of-value projects reach a go/no-go decision, and at least one is in production and in regular use on the desk.\nYour production models are monitored, documented, and supportable by the wider team. Failures are found by monitoring, not by a trader.\nFailed experiments are stopped early and written up, so the team does not repeat them.\nYou have built reusable components, such as extraction pipelines and evaluation harnesses, that the rest of the team uses.\nThe Environment\nVitol is one of the world’s largest independent energy traders, and Houston is one of its core trading offices. The Applied ML team sits close to the desks, so feedback is fast and the people using your work are just a few desks away.\nWe look for scientists and engineers who own outcomes, not just tickets. You will have room to choose your approach, and you will be expected to deliver work that traders can rely on.\nComprehensive benefit coverage includes:\nMedical\nDental\nVision\nPaid Vacation\n401k with company contributions\nLife insurance\nShort-term & Long-term disability\nAll your information will be kept confidential according to EEO guidelines.","description_format":"text","description_chars":5599,"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":[{"language":"English","level":"All levels","optional":false}]},"benefits":["401k plan","Life insurance"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Fossil Fuels","Oil & Gas"],"lifecycle":[{"event":"open","at":"2026-11-13T20:51:37Z"}],"visa":[{"country":"US","licensed_sponsor":true,"adverts_offering_sponsorship_24m":0,"sanctioned_now":false,"evidence":"H-1B filings in 12 months: 5 · green card filings: 1","filings_12m":5,"filings_prev_12m":10,"green_card_filings_12m":1,"median_offered_wage_usd":150000,"route":null,"cap_exempt":false,"checked_at":"2026-11-12T07:36:15+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":2}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":57,"reasons":["conf:1","win:early"],"computed_at":"2026-11-13T22:04:07Z"},"pay":null,"html_url":"https://alion.io/job/vitol-com-senior-data-scientist-applied-ml","json_url":"https://alion.io/job/vitol-com-senior-data-scientist-applied-ml.json","meta":{"generated_at":"2026-11-13T22:04:07Z","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":44002,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-14T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.1,"usd":0.01,"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":691744},"rest":"https://alion.io/mcp/rest/get_company?id=691744"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fvitol-com-senior-data-scientist-applied-ml"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"free","price":{"credits":0,"usd":0},"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%2Fvitol-com-senior-data-scientist-applied-ml"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.1,"usd":0.01},"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%2Fvitol-com-senior-data-scientist-applied-ml"},{"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/vitol-com-senior-data-scientist-applied-ml\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fvitol-com-senior-data-scientist-applied-ml"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":4282560}},{"tool":"search_jobs","arguments":{"company":"vitol.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":4282560},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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