Data Scientist

Are you looking for a role where you can use your data scientist experience to make a difference in the automotive industry? LER TechForce is an industry leader in embedded controls, software, functional safety, and engineering IT talent, with over 20 years of experience serving customers across North America. We are seeking a proactive Data Scientist with 4+ years of experience to join our team. This role involves collaborating with Product Owners and Data Engineers to develop advanced algorithms and digital features, primarily working with time series data from various controllers transmitted via telematics, focusing on descriptive and predictive modeling to optimize equipment uptime and minimize downtime. Our products serve the Mining and Power Generation sectors worldwide, requiring expertise in data science with a controls engineering background in a global, cross-functional environment.

Responsibilities

• Develop new or modify existing algorithms and features that leverage Python, SQL, Databricks, and PySpark to enhance data analytics and processing capabilities.
• Design, implement, and validate descriptive and predictive models using time series data to assess and predict equipment downtime and failure modes.
• Tune existing machine learning models.
• Collaborate with Product Owners and Data Engineers to define requirements, gather and curate data, and develop digital solutions to enhance equipment reliability and performance.
• Process and curate data from controllers across telematics systems, ensuring data quality and readiness for model training and development.
• Analyze, interpret, and model time series data to drive actionable insights for product performance and predictive maintenance.
• Communicate findings, challenges, and solutions effectively with global teams, stakeholders, and non-technical audiences.

Ideal candidate

What you’ll get

What you’ll need to be successful

Note : Referrals increase your chances of interviewing at LER TechForce. Mexico City Metropolitan Area 2 weeks ago.

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