Data Scientist

Data Scientist

Job Overview

Exponential growth in adoption and deployment of connected cars and devices is bringing previously unavailable datasets to market – at scale and in real-time. Stellantis, one of the largest global car makers and the parent company of dozens of iconic brands including Jeep, Fiat, Maserati, Peugeots, and more, has created a new Data BU to harness sensor and other data from 10s of millions of connected vehicles as well as that from IoT/connected devices from external sources to build data products and services that can power hundreds of brand-new b2b and b2c applications, services, and decision-making across industries.

Mobilisights, a Stellantis Data BU is seeking a talented and innovative Data Scientist to join our team. The ideal candidate will have experience with real-time/streaming data, telematics, and the automotive domain, with a strong background in machine learning and AI. In this role, you will leverage advanced data science techniques to develop predictive models, uncover insights, and drive data-driven decision-making.

A truly global company, we have headquarters in Amsterdam, Paris, Turin, and Auburn Hills. We also have technology hubs on the east and west coast of the United States, in South America and India. These locations are the nerve center of our company, where the best ideas combine with unrivaled rigor to create the biggest and best automotive experiences in the world.

Key Responsibilities:

• Machine Learning & AI:

• Develop and implement machine learning models and algorithms for predictive analytics, anomaly detection, and classification tasks using real-time and historical data.

• Experiment with and deploy advanced AI techniques, including deep learning, reinforcement learning, and natural language processing, as applicable to automotive data.

• Data Science & Modeling:

• Design and build statistical models to analyze telematics data and vehicle performance, including regression, clustering, and time-series analysis.

• Utilize feature engineering techniques to extract relevant features from complex datasets and improve model accuracy.

• Real-Time Data Processing:

• Create and maintain scalable data pipelines to handle real-time streaming data from automotive sensors and telematics systems.

• Implement real-time analytics solutions to monitor and respond to data changes instantaneously.

• Automotive Domain Expertise:

• Apply domain knowledge to develop models that enhance vehicle performance, optimize driver behavior, and predict maintenance needs.

• Collaborate with automotive engineers to integrate data science solutions into vehicle systems and applications.

• Data Visualization & Interpretation:

• Build interactive dashboards and visualizations to convey complex data insights and model results to stakeholders.

• Interpret model outputs and translate them into actionable recommendations for product development and business strategy.

• Research & Innovation:

• Stay current with the latest developments in data science, machine learning, and AI to bring cutting-edge techniques and tools to the team.

• Conduct research to explore new methodologies and technologies that could be applied to automotive data science challenges.

• Collaboration & Communication:

• Work closely with cross-functional teams, including engineers, product managers, and data engineers, to align data science efforts with business goals.

• Present findings and insights to technical and non-technical audiences, including executive leadership.

Qualifications:

• Education:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or a related field.

• Experience (Relevant 5+ years):

• Proven experience in data science roles with a focus on machine learning, AI, and predictive modeling.

• Experience working with real-time/streaming data and telematics is highly desirable.

• Background in the automotive industry or with automotive data is a plus.

• Skills:

• Proficiency in programming languages such as Python, R, or Java.

• Hands-on experience with machine learning, deep learning frameworks and libraries (e.g., Scikit-learn, TensorFlow, PyTorch, Keras).

• Knowledge of statistical analysis and modeling techniques (e.g., regression, classification, clustering).

• Familiarity with data processing tools and frameworks (e.g., Apache Kafka, Apache Flink, Spark).

• Strong skills in feature engineering, model evaluation, and algorithm tuning, MLOps.

• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn, ggplot) and techniques.

• Excellent problem-solving abilities, with a knack for deriving actionable insights from complex datasets.

• Preferred:

• Experience with deep learning and reinforcement learning techniques.

• Knowledge of vehicle communication protocols (e.g., CAN bus) and telematics systems.

• Familiarity with cloud-based machine learning services and platforms (e.g., AWS SageMaker, Google AI Platform, Azure ML).