{"id":3388661,"url":"https://alion.io/job/teva-machine-learning-operations-analyst","title":"Machine Learning Operations Analyst","company":{"id":1822915,"name":"Teva","domain":"teva.com","url":"https://alion.io/company/teva-com","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"B","score":79,"open_postings":24,"ghost_share":0,"stale_share":0.833,"repost_share":0,"time_to_fill_p50_days":50,"computed_at":"2026-10-31T05:58:55Z"}},"role":"Analytics","role_family":"Analytics","seniority":"junior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Zagreb, Croatia"],"countries":["HR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":20000,"max_usd":48000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1876},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"CAPA","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Incident Management","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-12T15:31:33Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-10-31T21:16:00Z","board_verified":true,"closed_at":null,"days_open":19,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":19},"description":"We Are Teva\nWe’re Teva, a leading innovative biopharmaceutical company, enabled by a world-class generics business. Whether it’s innovating in the fields of neuroscience and immunology or delivering high-quality medicine worldwide, we’re dedicated to addressing patients’ needs now and in the future. Here, you will be part of a high-performing, inclusive culture that values fresh thinking and collaboration. You'll have the room to grow, the flexibility to balance life with work, and the opportunity to better health worldwide, together.\nOur Team, Your Impact\nThe ML Operations Analyst is responsible for maintaining the day-to-day operation of machine learning production pipelines. This role ensures data and model pipelines execute successfully, investigates production failures, resolves issues, maintains model documentation, and supports continuous improvement of model reliability.\nThe role serves as the first line of support for production analytics solutions and works closely with Data Scientists and Data Engineers.\nHow You’ll Spend Your Day\nProduction Monitoring & Support\nMonitor daily, weekly, and monthly model execution schedules.\nMonitor ETL and data pipelines supporting machine learning models.\nInvestigate and resolve production failures.\nTroubleshoot data quality, integration, and system issues.\nRestart and recover failed jobs and workflows.\nEscalate complex issues when necessary.\nPipeline Maintenance\nMaintain production model pipelines.\nValidate data availability and completeness.\nEnsure model inputs and outputs meet quality standards.\nSupport model refresh and retraining processes.\nMaintain automated schedules and workflow orchestration tools.\nIncident Management\nPerform root cause analysis for production incidents.\nTrack and document recurring issues.\nImplement corrective and preventive actions.\nDocumentation & Governance\nMaintain model inventory and documentation.\nSupport model audit and governance requirements.\nEnsure documentation remains current after production changes.\nContinuous Improvement\nIdentify opportunities to automate manual support processes.\nImprove monitoring, alerting, and operational efficiency.\nAssist with deployment of new analytical models into production.\nSupport testing and validation activities\nSupport model performance tracing and monitoring\nYour Skills and Experience\nBachelor's degree in Computer Science, Data Science, Statistics, Engineering, Information Systems, or related field.\n2+ years supporting analytics, data, or machine learning applications.\nExperience supporting production systems.\nExperience troubleshooting data pipelines and automation workflows.\nProgramming: Python, SQL, Git\nData & Analytics: - ETL processes - Data quality validation - Model monitoring\nCloud / Platforms: Experience with one or more: Databricks, Azure, MLflow, Azure Data Factory\nHow We’ll Take Care of You\nAt Teva, better health starts from within, and that includes you. From day one, you’ll be supported with benefits designed to help you thrive in and out of work. This includes generous annual leave, reward plans, flexible working schedules (dependent on role), access to tailored health support, and meaningful ways to give back to the community. When it comes to your career, you’ll be encouraged to explore, evolve, and shape your path. Twist, our one-stop shop for career development platform, gives you access to a wide range of possibilities, from learning programs and short-term projects to opportunities for internal growth. Here, you’ll be part of a culture that empowers you to reach your goals and prioritize your wellbeing every step of the way.\nAlready Working @Teva?\nMake sure to apply through our internal career site on Twist-your one-stop shop for career development\nTeva’s Equal Employment Opportunity Commitment\nTeva Pharmaceuticals is committed to equal opportunity in employment. It is Teva's global policy that equal employment opportunity be provided without regard to age, race, creed, color, religion, sex, disability, pregnancy, medical condition, sexual orientation, gender identity or expression, ancestry, veteran status, national or ethnic origin or any other legally recognized status entitled to protection under applicable laws. We are committed to a diverse and inclusive workplace for all. If you are contacted for a job opportunity, please advise us of any accommodations needed to support you throughout the recruitment and selection process. 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