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Principal Data Science Manager

The Principal Data Science Manager is responsible for creating and implementing high-impact data science deliverables. This position understands stakeholder needs at the enterprise level, develops hypotheses, defines solutions, develops models, tests results and collaborates to deliver solutions.

This position also manages a team of direct reports, establishes team goals and objectives, evaluates performance progress and fosters a culture of continuous learning. 

Essential Functions:

  • Develop a deep understanding of Arrive’s core business processes, business KPIs, and how these interact to create enterprise value
  • In collaboration with engineering and the rest of the data org, orchestrate the implementation of near-real-time, online production models leveraging SQL and Python
  • Effectively work across stakeholders, product, technology, and the data org to identify business problems, develop hypotheses, define data science solutions, develop models, test results, and collaborate to deliver solutions
  • As a recognized expert in their technical area of focus, ability to influence strategic decisions across the organization relevant to their area.
  • Work closely with key business stakeholders to identify needs, create hypotheses, investigate data science solutions, test results, and work with engineering to put into production
  • Effectively estimates effort and delivers results on time while also identifying potential roadblocks to achieving successful results.
  • Effectively leverages cloud-based resources to perform data analysis, data cleaning, data preparation, and feature engineering to identify patterns and develop machine learning models to automate decision-making and generate insights
  • Stay abreast of emerging data science research and trends and not only continuously upskill your own capabilities as new methods and techniques are developed but enable the entire Data Science team to upskill and develop
  • Develops new insights and identifies new, novel techniques that are shared across the Data Org
  • Management Experience: 2+ years of experience having a team of Data Scientists report directly to them
  • Ensures work product has sufficient quality and is delivered in a timely manner
  • Provides coaching on performance, inspires team members to grow, and encourages ownership while also enabling opportunities for risk-taking
  • Encourages appropriate work/life balance and demonstrates interest in the well-being and success of team members
  • Generates a positive work experience and provides team members with a place to have fun and create connections with other team members

Skills and Education:

  • Demonstrated success in a fast-paced, business-results-driven culture by delivering significant, quantifiable business results
  • Bachelor’s Degree in a quantitative field (Statistics, Computer Science, Engineering, Mathematics) and 7+ Years of experience in a Data Science role OR Masters/Ph.D. and 5+ Years of experience 
  • Fluency in English and Spanish required 
  • Experience developing machine learning models and data science solutions using SQL and Python for production implementation
  • Extensive knowledge of statistics and machine learning methods with significant experience using machine learning techniques such as random forest and boosted trees for regression and classification 
  • Strong written & oral communication skills and an ability to present effectively to stakeholders of all levels
  • Experience thriving within an Agile environment
  • Experience working in cloud environments and specifically with Microsoft Azure tools and technologies is a plus
  • Experience in the Logistics or Transportation Industry is a major plus.

Supervisory Responsibility:

  • This position manages a team of direct reports.

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