Data Scientist

A startup in the automotive cybersecurity field, focusing on the realms of Automotive and Connected Car, provides a cloud platform for cybersecurity and data analysis for the automotive industry.

The company recently completed a Series C funding round, raising a total of over $100 million, and is significantly stable moving forward. Strategic investors from the automotive sector support the company, which already has paying customers including car manufacturers, insurance companies, and fleet management firms.

The company is located in the Sharon area near a train station and operates on a hybrid model with two days of remote work per week.

About the role

• Involves Data Science work from research to production.
• Includes theoretical and research-based work to find creative solutions to a variety of problems.
• Primarily involves tabular data, sequential and time series data, and data streaming.
• Coding is done in Python.
• Develops ML/DL/AI algorithms using Pandas, Polars, NumPy, SciPy, Scikit-learn, TensorFlow, Keras, PyTorch, and SQL.
• The team is cohesive and has an amazing atmosphere.

Responsibilities

• Conduct in-depth research on large and diverse automotive live streaming tabular datasets
• Explore, design and deploy cutting-edge models or algorithms solutions for prediction purposes and anomaly detection
• Collaborate closely with domain experts and peers to research and implement models and algorithm flows that best fit requirements
• Partner with the data engineering and development teams to devise innovative solutions for productization
• Encourage collaboration and knowledge-sharing within the data science team

Requirements

• 5 years of relevant industry experience in data science or machine learning
• Education: MSc in Math/EE/CS/Statistics or related fields
• Demonstrated research expertise in the tech industry or published academic papers
• Profound understanding and hands-on expertise in mathematics, statistics, machine/deep learning, and data mining
• Strong coding and software engineering experience focusing on advanced proficiency in Python, especially in data science libraries such as Pandas, Polars, NumPy, SciPy, Scikit-learn, and others
• End-to-end experience in leading the development of AI/DS/ML products or features
• Demonstrated experience in working streaming data (including sequential/time series) and implementing corresponding algorithms/models in a production environment, whether in batch processing or real-time scenarios
• Solid experience in deep learning, utilizing platforms such as TensorFlow, Keras, PyTorch, etc.
• Proficiency in SQL