{"id":1186323,"url":"https://alion.io/job/bosch-data-scientist-fmdiv-","title":"Data Scientist (f/m/div.)","company":{"id":132,"name":"Bosch","domain":"bosch.com","url":"https://alion.io/company/bosch","size_band":"5000+","is_staffing_agency":false,"is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":75,"open_postings":668,"ghost_share":0,"stale_share":0.987,"repost_share":0,"time_to_fill_p50_days":23,"computed_at":"2026-09-24T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Braga, Portugal"],"countries":["PT"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":36000,"max_usd":82000,"period":"year","method":"role_country_seniority_unknown","sample_n":15},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"Machine Learning","optional":false},{"name":"CI/CD","optional":true},{"name":"Databricks","optional":true},{"name":"Git","optional":true},{"name":"Matplotlib","optional":true},{"name":"NumPy","optional":true},{"name":"Pandas","optional":true},{"name":"Plotly","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"Scikit-learn","optional":true},{"name":"SciPy","optional":true},{"name":"Seaborn","optional":true},{"name":"SQL","optional":true},{"name":"TensorFlow","optional":true},{"name":"Time Series Forecasting","optional":true}],"status":"live","first_seen_at":"2026-09-24T10:43:54Z","employer_posted_date":"2026-09-24","last_verified_at":"2026-09-24T21:09:29Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"The Bosch Group has more than 400 000 employees around the world, present in 60 countries, and we are proud to impact people’s lives and to work towards a more sustainable future.\nBosch Car Multimedia, S.A. belongs to the Automotive Electronics division and is focused on making the vehicles our third living space. About 3.600 associates are committed to develop and produce high quality technology that shape change in mobility worldwide. The company' success lies in its highly specialized and innovative team, and on the technological know-how which makes Bosch the leading supplier in the automotive market.\nAt Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference in mindsets, cultures, generations, identities and perspectives. Everyone should bring their authenticity and work together respectfully. Bosch is an employer that values diversity and equal opportunities. We welcome applications from people with disabilities and we can provide reasonable accommodations during the recruitment process and in the performance of professional activity. By including everyone and ensuring equal opportunities we unleash our full potential.\n As a Data Scientist, you will help shape the future of manufacturing by transforming complex engineering and production challenges into data-driven solutions that create measurable business value.\nWorking at the intersection of Artificial Intelligence, Machine Learning and Industrial Analytics, you will analyse manufacturing data to uncover patterns, identify root causes and drive process improvements. Your insights will support smarter decisions, enhance product quality and increase operational efficiency across manufacturing environments.\nYou will develop and validate AI/ML models and advanced analytics solutions for use cases such as:\nQuality improvement and process optimization\nAnomaly detection and root cause analysis\nPredictive maintenance and failure prediction\nProductivity and yield improvement\nProcess stability monitoring\nDecision support for engineering and manufacturing teams\nAs part of a multidisciplinary team, you will collaborate closely with Process Experts, Technology Development Engineers, Data Analysts, MES/PLC specialists, Data Engineers, MLOps teams, IT professionals and business stakeholders to ensure solutions are scalable, explainable and aligned with real operational needs.\nYou will contribute throughout the entire solution lifecycle, from problem definition and data exploration to model development, validation, deployment support and continuous improvement. In addition, you will help standardize and reuse analytical methods, models and best practices across projects and locations, supporting Bosch's digital transformation journey and Industry 4.0 initiatives.\n What distinguishes you:\nEducation\nMSc or PhD in Data Science, Artificial Intelligence, Machine Learning, Computer Science, Mathematics, Statistics, Engineering, Physics or a related field.\nAcademic or professional background in machine learning, statistics, optimization or data-driven problem solving.\nExperience\nExperience developing Machine Learning, Artificial Intelligence or Advanced Analytics solutions.\nHands-on experience working with complex datasets in industrial, engineering, manufacturing or technical environments.\nExperience contributing to end-to-end data science projects, including data preparation, model development, validation and deployment.\nExposure to manufacturing, process development, industrialization, quality improvement or equipment-related analytics is considered an advantage.\nKnow-how\n1. Machine Learning & Advanced Analytics\nKnowledge of machine learning methods, including regression, classification, clustering, anomaly detection, forecasting and optimization.\nExperience applying techniques such as feature engineering, model evaluation, hyperparameter tuning and model explainability.\nFamiliarity with deep learning approaches is a plus.\n2. Statistics & Experimental Methods\nKnowledge of statistical analysis, probability and experimental data analysis.\nExperience with hypothesis testing, regression analysis, statistical significance and data interpretation.\nUnderstanding of process variability, capability analysis, performance indicators and Design of Experiments (DoE).\n3. Programming & Data Science Tools\nProficiency in Python and good knowledge of SQL.\nExperience with data science and machine learning libraries such as Pandas, NumPy, Scikit-learn, SciPy, Matplotlib, Seaborn, Plotly, PyTorch or TensorFlow.\nFamiliarity with Git and collaborative software development practices.\n4. MLOps & Industrial Deployment\nUnderstanding of MLOps concepts, including model versioning, testing, reproducibility, CI/CD and monitoring.\nExperience with cloud-based AI platforms, preferably Databricks, is an advantage.\nKnowledge of APIs, containers and deployment concepts is beneficial.\n5. Industrial Data & Manufacturing Systems\nExperience working with structured, semi-structured and time-series data.\nFamiliarity with manufacturing systems and data sources such as MES, PLC, SCADA, Historian systems, test systems or production databases.\nUnderstanding of manufacturing KPIs such as OEE, yield, scrap, downtime, cycle time, rework and process capability is an advantage.\nLanguages\nFluent English, written and spoken.\nWorking Style and Methods\nStructured and analytical approach to problem-solving.\nAbility to transform complex challenges into practical, scalable solutions.\nStrong collaboration skills with both technical and non-technical stakeholders.\nClear communication skills and ability to present analytical insights in an actionable way.\nStrong focus on quality, reusability and continuous improvement.\nPersonality\nCurious and eager to learn new technologies and methodologies.\nProactive, collaborative and solution-oriented mindset.\nStrong sense of ownership and accountability.\nPassion for data, innovation and making a tangible impact in industrial environments.\n Work #LikeABosch includes:\nFlexible work conditions\nHybrid work system\nExchange with colleagues around the world\nHealth insurance\nMedical office (psychology and general clinic) & Social Services Office on site\nTraining opportunities (p.e., technical training, foreign languages training) & certifications\nOpportunities for career progression and continuous professional development\nAccess to great discounts in partnerships and Bosch products\nSports and health related activities\nGreat access to public transports\nFree transport from Porto\nFlexible benefits platform\nFree parking lot\nCanteen\nSuccess stories don´t just happen. They are made...\nMake it happen! We are looking forward to your application!","description_format":"text","description_chars":6884,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[{"language":"English","level":"Advanced (C1)","optional":false}]},"benefits":["Flexible schedule","Health insurance","Hybrid work","Professional development"],"hiring_locations":[{"name":"Portugal","iso":"PT","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Sensors","Tools & DIY Supplies","HVAC & Refrigeration","Automotive Components"],"lifecycle":[{"event":"open","at":"2026-09-24T14:56:20Z"}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":23,"reasons":["conf:2","win:early","comp:brand"],"computed_at":"2026-09-24T23:30:08Z"},"pay":null,"html_url":"https://alion.io/job/bosch-data-scientist-fmdiv-","json_url":"https://alion.io/job/bosch-data-scientist-fmdiv-.json","meta":{"generated_at":"2026-09-24T23:30:08Z","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":1632,"day_limit":5000,"remaining_today":3368,"minute_limit":60,"resets_at":"2026-09-25T00:00:00Z"}}}