{"id":3627790,"url":"https://alion.io/job/sperry-rail-data-scientist-decision-quality","title":"Data Scientist, Decision Quality","company":{"id":4495570,"name":"Sperry Rail","domain":"sperryrail.com","url":"https://alion.io/company/sperry-rail","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Rippling","truth_index":{"grade":"B","score":75,"open_postings":23,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-08T05:47:12Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Shelton, United States"],"countries":["US"],"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":"Agile","optional":false},{"name":"CI/CD","optional":false},{"name":"Git","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"Human-in-the-Loop","optional":true}],"status":"live","first_seen_at":"2026-08-20T21:29:04Z","employer_posted_date":"2026-08-20","last_verified_at":"2026-11-08T16:40:53Z","board_verified":true,"closed_at":null,"days_open":79,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":79},"description":"About Sperry:\nSperry Rail is on a mission-critical journey to revolutionize the Rail Flaw Detection industry. Through the continuous development of cutting-edge diagnostic technologies and AI-assisted analysis, we are transforming railway safety worldwide. Our global engineering teams work collaboratively to develop step-change technologies that define Sperry as the unparalleled market leader.\nFor nearly a century, we have repeatedly modernized and improved rail diagnostics through our relentless pursuit of improvement. Determined is an understatement. We are obsessed with advancing science and raising the bar on what’s possible with our ever-improving suite of products and service offerings.\nEmboldened through the shared values of honesty, accountability, passion, integrity, and teamwork, we are driven by the challenge and bridging concepts with fruition. Each technologist entering Sperry imprints themselves into our brand and further galvanizes a culture of innovation and advancement. Allow us to be clear, Thought Leaders are welcome!\nWe are agile and hungry and invite those with similar passions to join us in challenging the status quo and bringing new ideas to the market. Fast-paced, high-touch with a distinct sense of purpose. We offer more than a job; we offer an opportunity to be part of something different.\nRole Summary\nSperry's detection pipeline is part machine and part human. A neural network scans ultrasonic and electromagnetic test data collected from track and puts forward candidate defects. Trained analysts then review that output and decide what is real, what is not, and what gets sent to the railroad. Those decisions are the last judgment before a defect either reaches a customer or does not. Your job is to model that decision. Given what the analyst could see at the moment they made the call, was the disposition right, and where the pipeline gets it wrong, what actually caused it. We already capture the decision logs, so the data is there from your first week. This is a quality role rather than an automation role. The point is to make analysts better and to show us where our training, our tooling, and our detection thresholds are letting people down. The first phase is retrospective scoring of decisions already made. Where it goes after that depends in large part on what you find. You are one of the first three seats in a new US data science team, alongside a lead who owns risk analytics and an engineer who puts models into production. The work is internal-facing and it sits close to the operation, so you will spend real time with the people whose decisions you are modeling.\nWhat We Expect From You\nWe expect an exceptional level of drive and ambition. You think beyond today's work to what the team and organization need next, champion bold ideas, and see them through. Your hunger is infectious - it inspires those around you to aim higher. You should be someone who puts the team first. You share credit openly, admit when you are wrong, and welcome feedback as an opportunity to grow. This role asks you to tell an organization things about its own performance that it may not want to hear, and that only works if people trust how you do it. This role requires a high degree of self-direction. You will manage complex work with minimal oversight, identify problems and solutions proactively, and may lead workstreams. You make well-reasoned technical decisions and escalate when there is genuine business impact. Strong analytical thinking is critical. You will work with imperfect labels, class imbalance, and outcomes that are only partly observable, and you need to be candid about what the data will and will not support. We would rather have a well-qualified answer than a confident one. You should be comfortable explaining a method to people who will not check your math but will act on your conclusion. Analysts, analysis managers, and operations leaders are your audience as much as other data scientists are.\nKey Responsibilities\nBuild and maintain retrospective scoring of analyst dispositions - given the data available at the time of review, how sound was the decision\nQuantify agreement and variation across analysts, shifts, territories, and test conditions\nSeparate analyst-attributable outcomes from detection-threshold, data-quality, and volume effects, so that the organization acts on the right cause\nIdentify the contributing factors behind missed and misinterpreted defects, and express them as a taxonomy the analysis organization can use rather than as individual scorecards • Work with analysis leadership to turn findings into feedback loops: training content, review guidance, tooling changes, and threshold recommendations\nDefine and maintain the measures of decision quality that hold up over time, and be clear about their limits\nDesign sampling and review studies where the passive data cannot answer the question\nWork with the detection and platform teams so the signals your models need are captured properly at source\nPresent findings to analysis leadership and to the wider engineering organization\nWrite clean, tested, well-documented code following engineering best practices\nParticipate in code reviews, sprint planning, and technical design discussions\nWrite and maintain documentation so the methodology is transferable rather than held tacitly\nRequired Skills & Qualifications\nStrong proficiency in Python (NumPy, Pandas, Scikit-learn, or similar) and SQL\nApplied statistics: classification metrics, sampling, inter-rater agreement, bias, and experimental design\nSupervised machine learning on imbalanced and imperfectly labeled data\nExperience evaluating decisions or predictions against ground truth that arrives late, partially, or not at all\nAbility to explain method and uncertainty to an operational audience and have them act on it\nFamiliarity with version control (Git), CI/CD pipelines, and agile development practices\nStrong problem-solving skills and ability to learn new technologies quickly\nGood communication skills - able to explain technical concepts to non-technical stakeholders\nA collaborative, team-first mindset aligned with our values of being Humble, Hungry, and Smart Qualifications and years of experience are indicative guidelines, not mandatory requirements. These criteria may be met through demonstrated competency or equivalent experience.\nDesirable Skills\nBachelor's degree in statistics, computer science, engineering, or a related quantitative field; advanced degree welcome\nHuman-in-the-loop machine learning, expert review systems, or label quality and annotation quality work\nModel evaluation and monitoring tooling\nHuman factors, quality management, or reliability engineering exposure\nSignal or sensor data, particularly ultrasonics, induction, or eddy current\nExperience in rail testing, NDT, or sensor-based inspection industries (ultrasound, eddy current, electromagnetic, etc.)","description_format":"text","description_chars":6929,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-11-02T20:14:07Z"}],"visa":[],"liveness":{"score":8,"band":"cold","label":"Long shot","p_open":1,"p_active":0.275,"p_room":0.28,"age_days":79,"expected_fill_days":25,"reasons":["conf:1","stale_co","win:tail","crowd:"],"computed_at":"2026-11-08T05:47:12Z"},"pay":null,"html_url":"https://alion.io/job/sperry-rail-data-scientist-decision-quality","json_url":"https://alion.io/job/sperry-rail-data-scientist-decision-quality.json","meta":{"generated_at":"2026-11-08T17:17:03Z","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":36325,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-09T00:00:00Z"}},"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":4495570},"rest":"https://alion.io/mcp/rest/get_company?id=4495570"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fsperry-rail-data-scientist-decision-quality"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":2,"usd":0.2},"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%2Fsperry-rail-data-scientist-decision-quality"},{"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%2Fsperry-rail-data-scientist-decision-quality"},{"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/sperry-rail-data-scientist-decision-quality\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fsperry-rail-data-scientist-decision-quality"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3627790}},{"tool":"search_jobs","arguments":{"company":"sperryrail.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3627790},"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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