{"id":1368835,"url":"https://alion.io/job/novelis-sr-data-scientist-apm","title":"Sr Data Scientist (APM)","company":{"id":1796558,"name":"Novelis","domain":"novelis.com","url":"https://alion.io/company/novelis","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"iCIMS","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Atlanta, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":115000,"max_usd":225000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":769},"experience_years_min":3,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Azure","optional":true},{"name":"Databricks","optional":true},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true},{"name":"Power BI","optional":true}],"status":"live","first_seen_at":"2026-09-28T03:26:08Z","employer_posted_date":"2026-09-28","last_verified_at":"2026-10-02T07:25:34Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Position Overview\nNovelis is one of the world leaders in aluminum recycling and rolling and a leading sustainable aluminum solutions provider. Driven by our purpose of shaping a sustainable world together, we work alongside our customers to provide innovative solutions to the aerospace, automotive, beverage packaging and specialty markets. Headquartered in Atlanta, Georgia, Novelis has approximately 13,000 employees in 32 operating facilities on 4 continents.\nResponsibilities & Qualifications\nThe Senior Data Scientist, (APM), supports the design, development, and deployment of data science and machine learning solutions that improve asset reliability, reduce unplanned downtime, and strengthen maintenance decision-making across Novelis’ manufacturing operations. Reporting to the Sr AI Engineer Leader of APM, this role partners with Operations, Reliability, Data Engineering, and AI Governance to translate industrial data into practical, actionable insights. The role develops and supports failure-prediction models, equipment health-monitoring logic, anomaly detection, and remaining-useful-life estimators for human decision support-not autonomous control.\nThis is a hands-on senior data science role with a reliability focus. The Senior Data Scientist helps convert prioritized APM use cases into reliable production solutions by combining statistical analysis, machine learning, time-series modeling, sensor data interpretation, and practical understanding of maintenance and reliability workflows. The role works within the technical direction, roadmap, and architecture established by the Sr AI Engineer Leader of APM while maintaining model quality, operational usability, and trust with plant stakeholders.\nCapability Alignment\nThis role is aligned to the APM delivery team within the Decision Intelligence & AI Enablement pillar and contributes to the following enterprise capabilities:\nIndustrial Data Science for Predictive Maintenance and Asset Reliability\nFailure Prediction, Remaining Useful Life Modeling, and Reliability Analytics\nEquipment Health Monitoring, Anomaly Detection, and Alert Quality Improvement\nTime-Series Modeling, Sensor Data Analysis, and Operational Context Interpretation\nModel Lifecycle Management for Industrial Analytics and Production Data Science\nResponsible AI Compliance in Operational Environments, aligned to AI Governance standards\nResponsibilities\nData Science Development & Reliability Analytics\nDevelop and deliver data science components of predictive maintenance and asset-reliability systems, including data preparation, feature engineering, exploratory analysis, model development, deployment support, and monitoring workflows.\nBuild, validate, and improve production-grade failure prediction models, equipment health scores, remaining-useful-life estimators, and anomaly detection methods that produce useful recommendations for maintenance and operations teams.\nApply statistical analysis, machine learning, time-series modeling, and reliability engineering judgment to solve industrial monitoring problems using appropriate evaluation methods and deployment patterns.\nAnalyze sensor, historian, maintenance, and operational data to identify asset behavior, failure patterns, signal quality issues, model drift, and opportunities to improve alert precision and credibility.\nSupport model lifecycle management through monitoring, retraining support, documentation, version control, testing, validation, and production troubleshooting.\nExecution Alignment & Cross-Functional Delivery\nDeliver assigned APM work in alignment with Novelis’ enterprise data and reliability priorities, including trusted data, operational reliability, metal flow optimization, sustainability goals, and operational efficiency.\nWork with reliability, operations, automation, information technology, and data engineering stakeholders to connect analytical findings to practical maintenance decisions and sustainable production use.\nSupport feature scoping, sprint execution, testing, deployment, user adoption, and continuous improvement activities aligned to the APM delivery roadmap and critical metric framework.\nAccountability Boundaries\nThis role delivers data science models, analyses, and engineering components within the roadmap, technical architecture, and technology direction owned by the Sr AI Engineer Leader of APM. It supports predictions and recommendations for maintenance and operations teams; people in Operations and Reliability make and complete the maintenance decisions and actions. This role contributes to the APM roadmap, model standards, analytics validation, production monitoring, and stakeholder feedback loops, but does not own enterprise architecture, autonomous closed-loop control, AI governance standards, core data platforms, business target definitions, data governance rules, master data policy, or data access configuration. Where a use case warrants autonomous closed-loop execution rather than human action, this role supports handoff to AI Automation for engineering and runtime ownership.\nMinimum Qualifications\nBachelor’s degree in Data Science, Computer Science, Engineering, Statistics, Applied Mathematics, Reliability Engineering, or a related field.\nMinimum of 3 years of experience in data science, machine learning, reliability analytics, predictive maintenance, industrial analytics, or related applied analytics work.\nExperience developing analytical or predictive models using time-series data, sensor data, equipment telemetry, maintenance records, or manufacturing process data.\nProficiency in Python, SQL, and common data science or machine learning libraries; ability to investigate data quality issues and explain model outputs to technical and non-technical stakeholders.\nStrong analytical, communication, and problem-solving skills, with interest in manufacturing, maintenance, reliability, or industrial decision support.\nPreferred Qualifications\nMaster’s degree or advanced certification in Data Science, Machine Learning, Statistics, Engineering, Reliability, or a related field.\nExperience in manufacturing, industrial operations, reliability engineering, maintenance analytics, or asset performance management.\nFamiliarity with industrial historians, condition monitoring data, edge or cloud analytics environments, Databricks, Power BI, Azure, or production model deployment practices.\nExperience translating analytical outputs into maintenance, reliability, or operational actions in partnership with plant stakeholders.\nFamiliarity with production data science, model deployment, or analytics platform practices, including tools such as Docker, Kubernetes, Azure, Databricks, or similar cloud and containerized deployment environments.\nPlease note that we are unable to provide visa sponsorship for this position. Candidates must be legally authorized to work in the United States without the need for current or future sponsorship\nWhat We Offer:\nNovelis' benefits say a lot about how we care for each other. Our employees and their families have many different needs. As a result, our benefits offer choices on many levels and are high in quality, driven by the marketplace, and affordable. In addition to core benefits, we provide these unique to the industry benefits:\nFamily Growth Programs: Paid parental Leave, Adoption Assistance, Fertility Treatment, Childcare Discount and Nursing Mom Support\nEmployee Assistance Programs: free resources available 24/7 to you and your family in the areas of mental health, family life, and career and financial guidance\nWellness Programs: incentives for wellness activities, wellness spending account, programs for building healthy habits, virtual physical therapy for joint, back, and pelvic health, health management programs and more.\nDiabetes Management Program\nPet insurance\nIdentity Theft Protection\nPerkSpot Discount Program\nTuition assistance and career development programs!\n#LI- AC1\n#LI- Hybrid\nLocation Profile\nNovelis’ Global Corporate and North America Headquarters is located in the Buckhead neighborhood of Atlanta GA employing around 700 people. Supporting it’s 31 operations worldwide Novelis’ corporate office is home to the executive leadership team and global functions that support the automotive beverage can and high-end specialties value streams. The City of Atlanta provides a diverse and family-friendly place to live with countless museums cultural organizations and educational institutions including the Georgia Aquarium Woodruff Arts Center CNN Center Georgia Tech and Mercedes-Benz Stadium. In the Atlanta area Novelis has strong community partnerships with Atlanta Habitat for Humanity GeorgiaFIRST and Agape Youth and Family Center in addition to many local museums and community groups.\nNovelis recognizes its talented and diverse workforce as a key competitive advantage. Novelis provides equal employment opportunities to all employees and applicants.All terms and conditions of employment at Novelis including recruiting hiring placement promotion termination layoffs recalls transfers leaves of absence compensation and training are without regard to race color religion age sex national origin disability status genetics protected veteran status sexual orientation gender identity or expression or any other characteristic protected by federal provincial or local laws.\nDisclaimer\nWe encourage all potential candidates to follow the protocols below and to be diligent when sharing any personal information:1. Check the job posting is live and valid via our careers page: Careers - Novelis2. Verify any communication with us by contacting our talent team at Careers - Novelis","description_format":"text","description_chars":9666,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":["Parental leave","Wellness"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Cybersecurity","Education","Professional Services"],"lifecycle":[{"event":"open","at":"2026-09-28T03:26:08Z"}],"liveness":{"score":47,"band":"ok","label":"Likely open","p_open":1,"p_active":0.852,"p_room":0.55,"age_days":4,"expected_fill_days":3,"reasons":["conf:11","velocity","win:tail","comp:brand"],"computed_at":"2026-10-02T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/novelis-sr-data-scientist-apm","json_url":"https://alion.io/job/novelis-sr-data-scientist-apm.json","meta":{"generated_at":"2026-10-03T02:08:38Z","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":2319,"day_limit":5000,"remaining_today":2681,"minute_limit":60,"resets_at":"2026-10-04T00:00:00Z"}}}