Advanced Analytics, Data Scientist

Key Skills

Python Programming, SQL, Regression Analysis, Azure, PowerBI, Apache Hadoop, Data science techniques, Data Mining, Jupyter Notebook, HDFS, R Programming, Algorithms, Clustering, Data Classification, SPARK Programming, Anomaly detection, Optimization, Gradient Boosting trees, Random forests, Advanced Analytics, K-Means clustering, Open source project tools

Job Description

You will be part of the powertrain simulation and application engineering organization. Your creative thinking and problem-solving skills will contribute to solving some complex challenges in the areas of data mining and optimization. You will be actively finding new ways to decrease costs and increase Uptime for our customers.

Responsibilities

• All steps of an analytics assignment, from data & business value exploration, data structuring, modeling, problem solving & recommendation. You will be able to deliver all steps independently, but also work closely in projects together with colleagues in Europe, India & Brazil.
• You will develop & implement methodologies to assist project leaders in making forecasts & predictions on quality or uptime performance of systems, components, and vehicle models.
• You will contribute with technical insight to the strategy & roadmap for the analytics area.
• Networking, relationship building and collaborating with our user groups and stakeholders, to assure we are on top of their challenges and are solving the most needed requirements first, as well as holding the longtime promises to assure a stable evolution of the Analytics area over time.

Qualifications

• Bachelor’s Degree in Engineering, Computer Science, Mathematics, Statistics, or equivalent minimum required.
• 4 years’ experience with relevant technical tools, SQL, Python, R, Azure Analytics Cloud, Jupiter Notebook, Power BI and Apache Spark.
• 1 years of exposure to data science projects with experience in problem definition, data preparation modeling and solution implementation
• Experience with machine learning algorithms for classification, regression, clustering, or anomaly detection including but not limited to: K-means, Random forest, Gradient boosting (XGBoost).

Preferred Qualifications

• Experience with open-source tools.
• Experience with the Hadoop ecosystem and HDFS.
• Experience with analyzing powertrain and engine from heavy-duty powertrain.
• Master’s Degree in Engineering, Computer Science, Mathematics, Statistics or equivalent.