Mercedes-Benz USA is looking to lead the design, development, and deployment of advanced analytics and AI solutions to drive strategic business outcomes, uncover insights, optimize operations, and enable data-driven decision-making across the organization.
Requirements
- Master’s degree with a strong academic background in statistics (e.g. mathematics, statistics, computer science, data mining, machine learning, operations research, physics, or a related quantitative discipline)
- 3+ (with master’s degree) years of experience in advanced analytics data analysis. Experience on the whole life cycle of model building for solving real-world complex problems.
- A deep understanding of statistical and predictive modelling concepts, including machine-learning or data mining approaches.
- Strong statistical modelling experience and data aggregation skills
- An expert in analysing large, complex, multi-dimensional data sets.
- Familiarity with cloud ecosystem (Azure Cloud, Hive, Spark, Kafka)
- Proficient in at least one IDEs such as VS Code or PyCharm (VS Code preferred)
- Proficient knowledge in SQL, Python and R (knowledge in Pyspark, SparkR or Scala is a plus), proficient in data visualization (i.e. proficient in Tableau or PowerBI)
- Familiarity with modern software development practices (Git, JIRA, CI/CD methods, MLOps)
Responsibilities
- Lead the end-to-end lifecycle of data science projects—from problem definition to model deployment and monitoring.
- Develop and operationalize machine learning models using Azure Databricks, MLFlow, Azure DevOps and Python.
- Design scalable data pipelines and workflows in collaboration with data engineering teams.
- Apply advanced statistical modeling, machine learning, and AI techniques to solve complex business problems.
- Create compelling data visualizations and dashboards using Power BI or Tableau.
- Promote reproducibility, version control, and automation using Azure DevOps, Git, and CI/CD pipelines.
- Drive best practices for putting ML/AI models into production, including monitoring, retraining, and performance evaluation.
Other
- Act as the primary point of contact for data science initiatives across business units.
- Translate complex analytical concepts into clear, actionable insights for stakeholders.
- Collaborate with cross-functional teams including product managers, engineers, and business analysts.
- Foster a culture of experimentation, continuous learning, and knowledge sharing within the data science community.
- Exceptional communication skills towards colleagues and management
- Excellent written and communications skills to report back the findings in a clear, structured manner are required.
- Experience in working in an agile team with internal and external resources.
- Strong analytical and problem-solving mindset
- Excellent communication and storytelling skills
- Ability to lead and mentor cross-functional teams
- Strategic thinking with a focus on business impact
- Comfortable working in a fast-paced, agile environment
- Fluent in English
