Data Engineer

Key Skills

AI technology, Azure, AzureML, Big Data Technology, clickHouse, Computer Vision (CV), Data science techniques, Data Visualization, Data Warehousing, Databricks, Google BigQuery, Machine learning techniques, Neural Networks, NumPy, Object detection, ONNX, Pose estimation, PowerBI, PySpark, Python Programming, PyTorch, R Programming, Risk Analytics, SPARK Programming, SQL, Statistical modeling, Synapse, TensorFlow, Teradata

Job Description

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

• 5+ years of professional consulting experience in Data Science or technology consulting or similar roles.

• 5+ 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

Qualifications

• 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

Fisker Inc. is an Equal Opportunity Employer; employment at Fisker Inc. is governed based on merit, competence and qualifications and will not be influenced in any manner by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability or any other legally protected status.