Job description

About Fisker Inc.

California-based Fisker Inc. is revolutionizing the automotive industry by developing the most emotionally desirable and eco-friendly electric vehicles on Earth. Passionately driven by a vision of a clean future for all, the company is on a mission to become the No. 1 e-mobility service provider with the world’s most sustainable vehicles. To learn more, visit – and enjoy exclusive content across Fisker’s social media channels: Facebook, Instagram, Twitter, YouTube and LinkedIn. Download the revolutionary new Fisker mobile app from the App Store or Google Play store.

Job Responsibilities

  • Work with large, complex datasets to solve complex analysis problems, applying advanced analytical methods (e.g., statistical and machine learning models) as needed. Conduct analysis that includes problem formulation, data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
  • A deep understanding of Enterprise SAAS business models and metrics like Pipeline, MQLs and Market Mix Modelling.
  • Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics, advocating for changes where needed.
  • Interact cross-functionally, making business recommendations (e.g., cost-benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
  • Develop and automate reports, iteratively build and prototype dashboards to provide insights at scale, solving for business priorities.

Skills And Experience

  • 3+ years of professional consulting experience in Data Science or technology consulting or similar roles.
  • 3+ years of experience in quantitative marketing data science, product data science, risk modeling, or similar field.
  • 3+ years of experience SQL/Teradata as well as modern analytical systems in Azure ecosystem, Spark SQL, PySpark
  • Strong proficiency in running statistical analyses in Python or R
  • Knowledge with data visualization tools such as Power BI preferred
  • Experience with Web Services and REST APIs is preferred
  • Experience leveraging a variety of services to act as data sources such as Azure Data Lake, Azure Synapse Analytics, Azure SQL, Azure EventHub/IoT Hub, etc.
  • Hands-on experience with analytics and big data technologies within Microsoft Azure, with experiences in tools such as Azure Data Factory, Azure Machine Learning, Azure Cognitive Services, Azure Databricks and Azure Synapse Analytics.
  • Knowledge and experience with leveraging distributed techniques for training and scoring machine learning models, ideally using Azure Databricks
  • Knowledge and experience with one or more cloud available Machine Learning frameworks and tools such as Tensor Flow, PyTorch, ONNX, NumPy, etc.
  • Knowledge and experience with Model Management, ideally using Azure ML service and/or MLFlow as well as deployment of models using Azure Kubernetes Service


  • Advanced degree in Computer Science, Mechanical engineering, Statistics or related STEM field.
  • 4+ years of Data or Machine learning Science experience working on highly complex problems in a dynamic setting
  • Strong programming skills, especially in Python, or C/C++ with 3+ years of relevant experience in a programming intensive role.

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