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Data Scientist

Data Scientist / Machine Learning Engineer

Technical Skills​

A data scientist should have strong technical skills in the following areas

  • Data analysis and statistical modeling: A data scientist should be able to analyze data and build statistical models to uncover insights and solve business problems.
  • Machine learning: A data scientist should have experience building and deploying machine learning models to drive business outcomes.
  • Data engineering: A data scientist should be able to work with data at scale and have experience with data pipelines, ETL processes, and data warehousing.
  • Programming: A data scientist should have strong programming skills, particularly in languages such as Python, R, or SQL.
  • Cloud Computing: Combine your DS/ML expertise with cloud computing proficiency.

Business Acumen​

A data scientist should be able to understand the business context and use data to drive business outcomes. This includes:

  • Understanding business goals and metrics: A data scientist should be able to understand the business goals and metrics that the company is trying to achieve and use data to drive progress towards those goals.
  • Problem-solving: A data scientist should be able to identify business problems and use data to develop solutions.
  • Industry knowledge: A data scientist should have knowledge of the industry the company operates in, including trends, challenges, and opportunities.

Communication​

A data scientist should be able to effectively communicate their findings and recommendations to stakeholders. This includes:

  • Presenting findings: A data scientist should be able to communicate complex findings and insights in a clear and concise manner.
  • Collaborating with stakeholders: A data scientist should be able to work effectively with stakeholders across the organization, including business leaders, engineers, and other data professionals.
  • Providing actionable recommendations: A data scientist should be able to provide recommendations based on data analysis that can be used to drive business decisions

Deliverable​

A data scientist is expected to:

  • Develop and deploy machine learning models that drive business outcomes.
  • Conduct exploratory data analysis to uncover insights and identify business problems.
  • Communicate findings and recommendations to stakeholders.
  • Collaborate with other data professionals, engineers, and business leaders to develop and execute data-driven strategies.