Assignment description

We are looking for motivated and experienced individuals to fill multiple roles in our client’s ML Engineering, Data Engineering, and Data Science teams. The successful candidates will be responsible for developing and implementing advanced models and algorithms to support energy estimation, battery modeling, vehicle-to-grid (V2G) usage modeling, state of charge (SoC) estimation, and driver modeling.

Responsibilities:

1. Collaborate with cross-functional teams to understand business requirements and develop solutions to address energy estimation challenges.
2. Design and implement machine learning models and algorithms for energy estimation and battery modeling using techniques such as regression, time series analysis, and neural networks.
3. Develop data pipelines and infrastructure to support the collection, storage, and analysis of large-scale datasets related to energy consumption, battery performance, and vehicle usage.
4. Conduct exploratory data analysis to identify patterns and insights that can inform the development of predictive models for V2G usage and SoC estimation.
5. Work closely with software engineers to integrate machine learning models into production systems and ensure scalability, reliability, and performance.
6. Collaborate with domain experts to refine and validate models based on real-world data and feedback.
7. Stay current with the latest research and advancements in machine learning, data engineering, and energy management to continuously improve their methodologies and techniques.
8. Communicate findings and recommendations to stakeholders through clear and concise reports, presentations, and visualizations.

Qualifications:

• Bachelor’s degree or higher in Computer Science, Electrical Engineering, Statistics, or a related field.
• Experience in machine learning, data engineering, or data science roles, with a focus on developing predictive models and algorithms.
• Proficiency in programming languages such as Python, R, or Java, and experience with libraries/frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Strong background in statistics, mathematics, and data analysis techniques.
• Experience with big data technologies and tools such as Hadoop, Spark, or Kafka.
• Familiarity with energy systems, battery technologies, and electric vehicles is a plus.
• Excellent problem-solving skills and the ability to work independently and collaboratively in a fast-paced environment.
• Strong communication skills and the ability to effectively communicate technical concepts to non-technical stakeholders.