Job

Senior Data Scientist (22-00493)

By April 18, 2022May 24th, 2022No Comments

Position Type: Direct Hire

Location: Remote

The Senior Data Scientist will draw insights from large and/or complex data sets to solve business problems addressed by use cases. The role will assess the applicability of different AI/Client methods for different use cases and independently lead model design and build to support business outcomes. The role will help drive advanced analytics thinking and methodologies by investigating various topics and sharing insights with broader data & analytics teams as well as business stakeholders

Responsibilities:

  • Gather business requirements, translate them into information solutions, design high-level model structures and demonstrate deep expertise in advanced analytics techniques (e.g., AI and Client) to design, prototype, and build solutions to business problems
  • Collaborate with Data Engineers to support data modeling and testing during projects
  • Ensure analytics tools and methods used in projects are robust and of the highest quality
  • Lead communication with other stakeholders to drive use case development and manage expectations on model limitations and lead times
  • Collaborate with business units to provide technical guidance related to AI/Client based models
  • Develop best practices for analytics (models, standards, tools) and mentor junior team members
  • Contribute to building the capabilities of advanced analytics, attending conferences, allocating time to investigate new topics, etc.

Requirements:

  • PhD/MS in a relevant field or related discipline (Computer Science, Mathematics, Engineering, etc.)
  • 3+ years experience in a statistical and/or data science role
  • Expertise in advanced analytical techniques (e.g., descriptive statistics, Client, optimization, pattern recognition, cluster analysis, segmentation analysis, etc.)
  • Experience using analytical tools and languages, (e.g., Python, SQL, Spark SQL etc.)
  • Experience working with large data sets, distributed computing tools (e.g., Azure Synapse, Snowflake); data transformation tools (e.g., Databricks, Azure Data Factory); Client technologies (e.g., Azure Machine Learning, AI platform, Tensorflow, SparkML, etc.)
  • Experience with data visualization tools (e.g., PowerBI)