[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-data-scientist-mwd-engineering":3,"similar-data-scientist-mwd-engineering":37},{"id":4,"slug":5,"title":6,"skills":7,"budget":22,"duration":22,"location":23,"onsitePercent":24,"contractType":25,"foundAt":26,"category":27,"description":31,"rawText":32,"webTitle":6,"webText":33,"language":34,"projectId":35,"sourceUrl":36},7384,"data-scientist-mwd-engineering","Data Scientist (m\u002Fw\u002Fd) Engineering",[8,9,10,11,12,13,14,15,16,17,18,19,20,21],"Python","SQL","Databricks","Data Analytics","Machine Learning","Pandas","NumPy","Power BI","Tableau","Big Data","Spark","Hadoop","Clustering","Regression",null,"Mannheim",100,"contracting","2026-06-02T06:25:48+00:00",{"id":28,"slug":29,"label":30},4,"data_analytics","Data & Analytics","Analyse und Auswertung großer Datenmengen zur Prozessoptimierung im Engineering-Umfeld. Entwicklung datengetriebener Methoden für Logistik- und Distributionsprozesse mit Python, SQL und Machine Learning. Erstellung von Datenmodellen und Visualisierung der Ergebnisse für Stakeholder.","Data Scientist (m\u002Fw\u002Fd) Engineering\nProjektnummer: FE28-20502-MA\nStandort: Mannheim, Baden-Württemberg\nArbeitsweise: Vor Ort\nLaufzeit: Keine Angabe\nStartdatum: Keine Angabe\n\nDas ist zukünftig dein Job:\n- Analyse und Auswertung großer Datenmengen zur Prozessoptimierung im Engineering-Umfeld\n\n- Entwicklung datengetriebener Methoden für Logistik- und Distributionsprozesse\n\n- Erstellung, Pflege und Optimierung von Datenmodellen mit Python, SQL und Databricks\n\n- Anwendung statistischer Analysen sowie Machine-Learning-Verfahren zur Mustererkennung\n\n- Extraktion relevanter Informationen aus heterogenen Datensätzen\n\n- Ableitung von Trends in operativen Prozessen mittels Data Analytics Tools wie Pandas oder NumPy\n\n- Präsentation von Analyseergebnissen und Visualisierung mittels Power BI oder Tableau für Stakeholder:innen\n\n- Entwicklung automatisierter Workflows zur kontinuierlichen Prozessverbesserung im Ersatzteilzentrum\n\nDas bringst du mit:\n- Abgeschlossenes Studium der Informatik, Wirtschaftsinformatik, BWL oder vergleichbare Fachrichtung\n\n- Berufserfahrung in der Logistikplanung mit Fokus auf Lager- und Distributionsprozesse wünschenswert\n\n- Fundierte Kenntnisse in Python, SQL sowie idealerweise Erfahrung mit Databricks-Plattformen\n\n- Praxiserfahrung mit Data Analytics Tools wie pandas, scikit-learn oder vergleichbaren Bibliotheken\n\n- Kenntnisse im Umgang mit Big Data Technologien zum Beispiel Spark oder Hadoop von Vorteil\n\n- Erfahrung in der Modellierung komplexer Datenstrukturen sowie deren Validierung durch Testszenarien \n\n- Kenntnis gängiger Methoden des maschinellen Lernens wie Clustering oder Regressionen \n\n- Verhandlungssichere Deutsch- und Englischkenntnisse\n\nSkills: Analyse, Auswertung, Big Data, Data Analytics, Entwicklung, Hadoop, Informatik, Logistik, Logistikplanung, Modellierung, Optimierung, Power BI, Prozessoptimierung, Präsentation, Python, SQL, Tableau, Validierung, Visualisierung, Wirtschaftsinformatik\n\nAnsprechpartner:\nMarie-Anne Engelskirchen\nTalent Acquisition Specialist\nFERCHAU GmbH, Niederlassung Mannheim\nLandteilstraße 33\n68163 Mannheim\n+49 621 40164-125\nmarie-anne.engelskirchen@ferchau.com","Wir suchen einen erfahrenen Data Scientist (m\u002Fw\u002Fd) für unser Engineering-Team am Standort Mannheim. In dieser Position analysieren und werten Sie große Datenmengen zur Prozessoptimierung im Engineering-Umfeld aus und entwickeln datengetriebene Methoden für Logistik- und Distributionsprozesse.\n\nIhre Hauptaufgaben umfassen die Erstellung, Pflege und Optimierung von Datenmodellen mit Python, SQL und Databricks sowie die Anwendung statistischer Analysen und Machine-Learning-Verfahren zur Mustererkennung. Sie extrahieren relevante Informationen aus heterogenen Datensätzen und leiten Trends in operativen Prozessen mittels Data Analytics Tools wie Pandas oder NumPy ab. Darüber hinaus präsentieren Sie Analyseergebnisse und erstellen Visualisierungen mittels Power BI oder Tableau für verschiedene Stakeholder. Ein weiterer Schwerpunkt liegt in der Entwicklung automatisierter Workflows zur kontinuierlichen Prozessverbesserung.\n\nWir erwarten ein abgeschlossenes Studium der Informatik, Wirtschaftsinformatik, BWL oder einer vergleichbaren Fachrichtung. Berufserfahrung in der Logistikplanung mit Fokus auf Lager- und Distributionsprozesse ist wünschenswert. Fundierte Kenntnisse in Python und SQL sowie idealerweise Erfahrung mit Databricks-Plattformen sind erforderlich. Praxiserfahrung mit Data Analytics Tools wie pandas oder scikit-learn sowie Kenntnisse im Umgang mit Big Data Technologien wie Spark oder Hadoop sind von Vorteil. Sie sollten Erfahrung in der Modellierung komplexer Datenstrukturen und deren Validierung mitbringen sowie gängige Methoden des maschinellen Lernens beherrschen. Verhandlungssichere Deutsch- und Englischkenntnisse runden Ihr Profil ab.","de","FE28-20502-MA","https:\u002F\u002Ftouch.ferchau.com\u002Fde\u002Fde\u002Fprojekt\u002F505528",{"items":38},[39,58,65,79,96,116,123,139,148,160,174,197,213,219,234],{"id":40,"slug":41,"title":42,"skills":43,"budget":22,"duration":22,"location":53,"onsitePercent":54,"contractType":55,"foundAt":56,"category":57},7362,"data-product-engineer-mwd-3","Data Product Engineer (m\u002Fw\u002Fd)",[9,44,15,45,46,47,48,49,50,51,52],"Datenmodellierung","SAC","SAP","ERP-Daten","Analytics Engineering","BI","Data Products","semantische Datenmodelle","Datenqualität","Hannover",50,"permanent","2026-06-01T19:11:08+00:00",{"id":28,"slug":29,"label":30},{"id":59,"slug":60,"title":42,"skills":61,"budget":22,"duration":22,"location":53,"onsitePercent":54,"contractType":55,"foundAt":63,"category":64},7361,"data-product-engineer-mwd-2",[9,44,15,46,45,48,50,47,62,52],"Semantische Datenmodelle","2026-06-01T19:06:03+00:00",{"id":28,"slug":29,"label":30},{"id":66,"slug":67,"title":68,"skills":69,"budget":22,"duration":75,"location":22,"onsitePercent":76,"contractType":25,"foundAt":77,"category":78},7358,"data-engineer-fuer-data-lakehouse-architektur-mit-snowflake","Data Engineer für Data Lakehouse Architektur mit Snowflake",[70,71,72,73,74],"Snowflake","Qlik Talend Cloud","Data Lakehouse","Data Vault","Star Schema","3 Monate +",0,"2026-06-01T17:30:21+00:00",{"id":28,"slug":29,"label":30},{"id":80,"slug":81,"title":82,"skills":83,"budget":22,"duration":91,"location":92,"onsitePercent":93,"contractType":25,"foundAt":94,"category":95},7336,"datawarehouse-experteentwickler-westerstederemote-mwd","Datawarehouse Experte\u002FEntwickler - Westerstede\u002Fremote (m\u002Fw\u002Fd)",[84,85,86,44,87,9,88,89,90],"Data Warehouse","ETL","PL\u002FSQL","Data Vault 2.0","BI-Tools","Qlik Sense","Datenbankdesign","3-4 Monate + Option auf Verlängerung","Westerstede",20,"2026-06-01T15:28:09+00:00",{"id":28,"slug":29,"label":30},{"id":97,"slug":98,"title":99,"skills":100,"budget":22,"duration":111,"location":112,"onsitePercent":113,"contractType":25,"foundAt":114,"category":115},7326,"senior-data-engineer-kubernetes-aws-python-mwd-90-remote","Senior Data Engineer (Kubernetes, AWS, Python) (m\u002Fw\u002Fd) 90% remote",[101,102,8,103,9,104,105,106,107,108,109,110],"Kubernetes","AWS","REST-API","Docker","Grafana","Kafka","Kinesis","OpenTelemetry","Polars","Prometheus","01.07.2026 – 31.12.2026","Berlin",10,"2026-06-01T15:11:01+00:00",{"id":28,"slug":29,"label":30},{"id":117,"slug":118,"title":119,"skills":120,"budget":22,"duration":111,"location":112,"onsitePercent":113,"contractType":25,"foundAt":121,"category":122},7325,"data-engineer-kubernetes-aws-python-mwd-90-remote-3","Data Engineer (Kubernetes, AWS, Python) (m\u002Fw\u002Fd) 90% remote",[101,102,8,103,9,104,105,106,107,109,110,108],"2026-06-01T15:06:14+00:00",{"id":28,"slug":29,"label":30},{"id":124,"slug":125,"title":126,"skills":127,"budget":22,"duration":22,"location":135,"onsitePercent":136,"contractType":25,"foundAt":137,"category":138},7323,"berater-mwd-data-governance","Berater (m\u002Fw\u002Fd) Data Governance",[128,129,130,131,132,52,133,134],"Data Governance","Datenarchitektur","Compliance","IT-Allgemeinwissen","Schnittstellen","Kommunikationsstärke","Projektmanagement","Köln",5,"2026-06-01T15:02:01+00:00",{"id":28,"slug":29,"label":30},{"id":140,"slug":141,"title":42,"skills":142,"budget":22,"duration":22,"location":53,"onsitePercent":54,"contractType":55,"foundAt":146,"category":147},7321,"data-product-engineer-mwd",[9,44,15,46,143,144,145,52],"Analytics","Data Engineering","Semantische Layer","2026-06-01T14:56:05+00:00",{"id":28,"slug":29,"label":30},{"id":149,"slug":150,"title":151,"skills":152,"budget":22,"duration":22,"location":22,"onsitePercent":76,"contractType":25,"foundAt":158,"category":159},7297,"data-engineer-sap-bw-to-microsoft-fabric-migration-mfd","Data Engineer - SAP BW to Microsoft Fabric Migration (m\u002Ff\u002Fd)",[153,154,15,155,85,156,157],"SAP BW","Microsoft Fabric","Data Modeling","Analytics Transformation","Data Platform Modernization","2026-06-01T13:20:55+00:00",{"id":28,"slug":29,"label":30},{"id":161,"slug":162,"title":163,"skills":164,"budget":22,"duration":22,"location":170,"onsitePercent":22,"contractType":171,"foundAt":172,"category":173},7250,"senior-data-analyst-mfd","Senior Data Analyst (m\u002Ff\u002Fd)",[165,9,8,15,155,85,166,167,10,168,169],"Data Analysis","Data Quality Management","Microsoft Azure","Data Warehousing","XML","Böblingen","temp_work","2026-06-01T10:40:59+00:00",{"id":28,"slug":29,"label":30},{"id":175,"slug":176,"title":177,"skills":178,"budget":191,"duration":192,"location":193,"onsitePercent":194,"contractType":25,"foundAt":195,"category":196},7247,"business-analyst-manufacturing-business-management","Business Analyst (Manufacturing Business Management)",[179,180,181,182,183,184,185,186,187,188,189,190],"Business Analysis","Manufacturing","Operations","Business Management","Requirements Gathering","Process Mapping","Functional Specifications","Agile","Scrum","Stakeholder Management","Thai","English","Negotiable","bis Dezember 2026","Bangkok",80,"2026-06-01T10:26:54+00:00",{"id":28,"slug":29,"label":30},{"id":198,"slug":199,"title":200,"skills":201,"budget":209,"duration":210,"location":22,"onsitePercent":76,"contractType":25,"foundAt":211,"category":212},7239,"power-bi-developer-consultant-mit-finance-controlling-know-how-gesucht-rein-remote-nur-near-offshore-2","Power BI Developer \u002F Consultant mit Finance- & Controlling-Know-how gesucht - rein remote - nur Near- \u002F Offshore",[15,202,203,204,205,206,207,46,9,44,186,208],"DAX","Finance","Controlling","Microsoft Power Platform","Power Apps","Power Automate","SAFe","75-85 EUR\u002Fh","01.07.2026 - 31.12.2026 + Verlängerungsoption","2026-06-01T10:21:08+00:00",{"id":28,"slug":29,"label":30},{"id":214,"slug":215,"title":200,"skills":216,"budget":209,"duration":210,"location":22,"onsitePercent":76,"contractType":25,"foundAt":217,"category":218},7238,"power-bi-developer-consultant-mit-finance-controlling-know-how-gesucht-rein-remote-nur-near-offshore",[15,202,203,204,205,206,207,46,9,44,186,208],"2026-06-01T10:20:51+00:00",{"id":28,"slug":29,"label":30},{"id":220,"slug":221,"title":222,"skills":223,"budget":22,"duration":22,"location":231,"onsitePercent":22,"contractType":25,"foundAt":232,"category":233},7187,"gis-arcgis-experte-mwd","GIS & ArcGIS Experte (m\u002Fw\u002Fd)",[224,225,226,227,228,229,230],"GIS","ArcGIS Pro","Geodaten","GIS-Datenanalyse","räumliche Datenbanken","ESRI-Technologien","Kartenprojekte","Frankfurt am Main","2026-06-01T08:16:16+00:00",{"id":28,"slug":29,"label":30},{"id":235,"slug":236,"title":237,"skills":238,"budget":22,"duration":251,"location":231,"onsitePercent":113,"contractType":25,"foundAt":252,"category":253},7177,"data-architect-mwd","Data Architect (m\u002Fw\u002Fd)",[239,240,241,242,243,244,245,246,247,248,249,130,250],"Data Architecture","KI-Governance","Enterprise Data Architecture","Metadatenmanagement","Master Data Management","DSGVO","EU AI Act","Jira","Confluence","SharePoint","Stakeholdermanagement","Dokumentation","12.06.2026 - 31.12.2026","2026-06-01T07:50:39+00:00",{"id":28,"slug":29,"label":30}]