- Company Name
- OPmobility
- Job Title
- GLOBAL IS / IT DATA PROFESSIONAL - DATA SCIENCE
- Job Description
-
**Job Title:** Global IS/IT Data Professional – Data Science
**Role Summary:**
Lead end-to-end data‑science initiatives within a global automotive technology organization. Design, develop, and deploy predictive models and analytics solutions that support product teams and data‑driven decision making, while ensuring model quality, scalability, and production readiness.
**Expectations:**
- Deliver high‑impact data‑science use cases aligned with business objectives.
- Maintain robust, production‑grade models and continuously improve model performance.
- Champion data‑science best practices, including MLOps, experimentation, and peer collaboration.
**Key Responsibilities:**
- Ideate, frame, and scope data‑science projects in partnership with Data Managers and Product Owners.
- Gather and clean data, design data pipelines, and apply statistical and machine‑learning techniques (regression, clustering, neural nets, decision trees, simulation).
- Build and validate models; set data‑quality controls and robustness metrics.
- Collaborate with Data Engineers to integrate models into production (MLOps pipeline, CI/CD).
- Monitor model performance, troubleshoot issues, and iterate improvements.
- Provide user support, training, and adoption metrics for model stakeholders.
- Lead peer reviews, experimentation, and Proof‑of‑Value studies; contribute to the internal Data Science community.
**Required Skills:**
- Strong background in Mathematics, Statistics, and Machine Learning.
- Proficiency with Python, R, Spark, and open‑source ML libraries (Scikit‑Learn, TensorFlow, PyTorch).
- Experience with SQL & NoSQL databases, data streaming (Kafka), and search platforms (ElasticSearch).
- MLOps expertise: model versioning, deployment, monitoring, and CI/CD pipelines.
- Data mining, cleaning, visualization, and automation tool development.
- Excellent analytical thinking, problem‑solving, and communication skills.
**Required Education & Certifications:**
- Degree in Mathematics, Applied Mathematics, Computer Science, Engineering, or a related quantitative field (Data Science preference).
- Professional certifications in Data Science, ML engineering, or relevant cloud technologies are advantageous.