{"id":776760,"url":"https://alion.io/job/fleetio-senior-applied-data-scientist-fleet-intelligence","title":"Senior Applied Data Scientist, Fleet Intelligence","company":{"id":3577,"name":"Fleetio","domain":"fleetio.com","url":"https://alion.io/company/fleetio","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":83,"open_postings":3,"ghost_share":0,"stale_share":0.667,"repost_share":0,"time_to_fill_p50_days":44,"computed_at":"2026-10-30T05:48:23Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["United States"],"countries":["US"],"hiring_countries":["US","CA","MX"],"hiring_countries_total":3,"salary":null,"salary_estimate":{"min_usd":117000,"max_usd":213000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":397},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"dbt","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false}],"status":"live","first_seen_at":"2026-09-11T21:20:12Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-31T01:38:44Z","board_verified":true,"closed_at":null,"days_open":49,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":49},"description":"A little about us…Fleetio is a modern software platform that helps thousands of organizations worldwide manage their fleet operations. Transportation technology is a hot market, and we’re leading the charge with raving fans and new customers signing up every day. We raised $450M in our Series D funding round in March of 2025 and are on an exciting trajectory as a company. Fleetio is also a proud founding member of the Rails Foundation!\nMore about our team and company:\nFleetio overview video: https://www.youtube.com/watch?v=YoXyXTFWbkg\nOur careers page: https://www.fleetio.com/careers\nFleetio is looking for a product-minded Senior Applied Data Scientist to join our Fleet Intelligence team. You will help turn years of fleet maintenance and operational data into trusted, actionable intelligence that helps customers anticipate what is ahead and make better decisions about usage, cost, availability, maintenance risk, and asset lifecycle.\nThis is an applied role at the intersection of data science, machine learning, analytics engineering, and product development. You will work closely with Product Managers, Designers, Software Engineers, and Data partners to identify valuable prediction problems, develop practical models, and bring them into customer-facing workflows. Your goal is to deliver intelligence that changes a decision, arrives early enough to act on, and communicates uncertainty honestly.\nYour initial mandate will be grounded in confirmed Fleet Intelligence work: utilization and tire intelligence, ROI measurement, existing predictive models, and the analytics foundations needed to support customer-facing intelligence. You will assess current model quality, establish credible baselines, and help the team ship useful capabilities while strengthening its data-science practices.\nOver time, you will help evaluate and shape opportunities for Predictive Fleet Intelligence, including projection, anticipation, and risk inference. You will help determine which opportunities are technically credible, valuable to customers, and ready to become durable product investments.\nMore About Our Team and Company\nWatch our culture videos: https://fleet.io/culture\nEngineering culture, interview process, and videos: https://www.fleetio.com/careers/engineering\nFleetio overview video: https://www.youtube.com/watch?v=IlvIbwZT3oU\nMore about the Fleetio platform: https://www.fleetio.com/features\nAPI docs: https://developer.fleetio.com\nThis is a remote opportunity and is open to candidates in the United States, Canada, or Mexico.\nWho You Are\nYou are an applied data scientist who enjoys working on ambiguous, high-value product problems. You can translate a customer or business decision into a measurable modeling problem, establish a credible baseline, and iteratively improve it. You know when straightforward statistics or deterministic projection is the right answer and when a machine learning approach is warranted.\nYou care deeply about correctness, explainability, and trust. You are comfortable communicating confidence intervals, limitations, and data gaps to technical and non-technical partners. You collaborate well with software and data engineers, but you can independently explore data, build production-quality models, define evaluation methods, and guide how model outputs should appear in a product experience.\nYou are pragmatic, product-minded, and outcome-oriented. You would rather ship a useful, well-calibrated forecast than an impressive model that does not change a customer decision.\nYour Impact\nHelp deliver near-term Fleet Intelligence initiatives, including tire intelligence, utilization intelligence, ROI measurement, existing predictive models, and the analytical foundations that support customer-facing intelligence.\nEvaluate and develop credible projections or predictive models for fleet usage, maintenance cost, availability, condition and failure risk, and asset lifecycle decisions as product direction and evidence mature.\nTranslate product questions into clear hypotheses, target variables, baselines, evaluation plans, and incremental delivery milestones.\nExplore Fleetio’s maintenance, usage, cost, work-order, telematics, warranty, and asset-history data to identify predictive signals and material data gaps.\nBuild, validate, and operationalize models from experimentation through production monitoring and iteration.\nDefine model-quality metrics, confidence thresholds, drift detection, and feedback loops appropriate to the cost and reversibility of the customer decision.\nPartner with Product and Design to make model outputs understandable, explainable, and actionable inside the workflows where customers already make decisions.\nEstablish reusable practices for experimentation, model documentation, validation, monitoring, and responsible claims about predictive performance.\nCommunicate findings, tradeoffs, risks, and recommendations clearly to technical partners, product leaders, and executives.\nShare knowledge through design reviews, documentation, pairing, and mentorship across Fleet Intelligence and adjacent teams.\nYour Experience\n5+ years of experience in applied data science, machine learning, statistical modeling, or a closely related role.\nA track record of developing and shipping models or decision-support systems that influenced real customer or business outcomes.\nStrong proficiency with DBT, Python, and SQL, including exploratory analysis, feature engineering, model development, and evaluation on large datasets.\nStrong grounding in statistics and machine learning fundamentals, including model selection, validation, calibration, uncertainty, bias, and error analysis.\nExperience with time-series forecasting, regression, classification, ranking, anomaly detection, survival or reliability analysis, or optimization; depth in several of these areas is more important than breadth across all of them.\nExperience taking models beyond notebooks into reliable production workflows, including versioning, testing, deployment, observability, performance monitoring, and retraining or refresh strategies.\nExperience using modern cloud data platforms and transformation workflows such as Snowflake, dbt, and orchestration tools in support of applied modeling work.\nAbility to identify data-quality limitations, recommend improvements, and collaborate with data engineers on pipelines and source reliability.\nExcellent written and verbal communication, particularly when explaining complex methods, uncertainty, and tradeoffs to non-specialists.\nExperience working cross-functionally with Product, Design, Software Engineering, and Data Engineering.\nConsidered a Plus\nExperience with fleet, transportation, maintenance, reliability, asset management, insurance, logistics, or another operational domain.\nExperience modeling maintenance cost, equipment failure, remaining useful life, warranty exposure, utilization, demand, or asset replacement decisions.\nFamiliarity with semantic layers and analytics tools such as ThoughtSpot or Cube.\nExperience designing experiments or evaluating recommendations when randomized testing is impractical.\nExperience contributing to customer-facing software products or collaborating closely with full-stack product engineers.\nGraduate study in statistics, data science, computer science, operations research, applied mathematics, economics, or a related quantitative field.\nBenefits \nMultiple health/dental coverage options (100% coverage for employee, 50% for family)\nVision insurance\nIncentive stock options\n401(k) match of 4%\nPTO - 4 weeks (increases at year two!)\n12 company holidays + 2 floating holidays\nParental leave - birthing parent (16 weeks paid) non-birthing (4 weeks paid)\nFSA & HSA options\nShort and long term disability (short term 100% paid)\nCommunity service funds\nProfessional development funds\nWellbeing fund - $150 quarterly\nBusiness expense stipend - $125 quarterly\nMac laptop + new hire equipment stipend\nFully stocked kitchen with tons of drinks & snacks (BHM only)\nRemote working friendly since 2012 #LI-Remote\nFleetio provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment. We celebrate diversity and are committed to creating an inclusive environment for all. All employment is decided on the basis of qualifications, merit and business need.\nThis application is not intended to and does not create a contract or offer of employment. Employment with Fleetio is at will.\nIf you have a disability or a special need that requires an accommodation to fill out the online application, please let us know by calling (205) 718-7500.","description_format":"text","description_chars":8638,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Parental leave","Professional development","Stock options","Vision insurance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"},{"name":"Canada","iso":"CA","kind":"country"},{"name":"Mexico","iso":"MX","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Fleet Management"],"lifecycle":[{"event":"open","at":"2026-09-11T23:14:13Z"}],"visa":[],"liveness":{"score":46,"band":"ok","label":"Likely open","p_open":1,"p_active":0.842,"p_room":0.55,"age_days":48,"expected_fill_days":44,"reasons":["conf:1","win:tail"],"computed_at":"2026-10-30T05:48:23Z"},"pay":null,"html_url":"https://alion.io/job/fleetio-senior-applied-data-scientist-fleet-intelligence","json_url":"https://alion.io/job/fleetio-senior-applied-data-scientist-fleet-intelligence.json","meta":{"generated_at":"2026-10-31T02:56:29Z","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":4160,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-01T00:00:00Z"}},"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":3577},"rest":"https://alion.io/mcp/rest/get_company?id=3577"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Ffleetio-senior-applied-data-scientist-fleet-intelligence"},{"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%2Ffleetio-senior-applied-data-scientist-fleet-intelligence"},{"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%2Ffleetio-senior-applied-data-scientist-fleet-intelligence"},{"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/fleetio-senior-applied-data-scientist-fleet-intelligence\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Ffleetio-senior-applied-data-scientist-fleet-intelligence"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":776760}},{"tool":"search_jobs","arguments":{"company":"fleetio.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":776760},"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. Docs: https://alion.io/developers"}}