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Principal Engineer, Data Science & Machine Learning

  • On-site
    • Seattle, Washington, United States
  • Development/QA/DevOps/IT

Job description

I. Solidify and scale the Leapfrog Data Science and Engineering Culture and Practice:

  • Lead definition and implementation of data, data science, and machine learning competency definitions at every level, and align with recruiting initiatives.

  • Manage the development lifecycle for data-centric projects using data to drive continuous improvements, with a strong focus on meeting the team's commitments given evolving business priorities and market/customer needs.

  • Lead the development of data-driven solutions, products and proofs of concept to acquire new business opportunities

  • Drive ongoing improvement in functional excellence and best practices (design sessions, code reviews, automation etc)

II. Lead Customer Accounts Where HIPAA Compliance Expertise is Necessary to Succeed

  • Lead current and future healthcare data-intensive projects that involve significant knowledge of healthcare interoperability and HIPAA compliance expertise to succeed.

  • Responsible to work with team to lead projects that require intensive retail data analytics

III. Ongoing stewardship of Leapfrog Technology's Data Capabilities Team

  • Work with other engineering leadership, and under the guidance of the Senior Vice President Engineering to hire, train, and deploy data engineers, machine learning engineers and data scientists

  • Meet regularly with data team members in both the US and Nepal to develop their skills and mentor them as they work on client projects

  • Lead the team with trainings and mentoring to evolve the team into a high-performing team of data scientists and machine learning engineers.

Job requirements

I. Education

  • Bachelor’s degree in Electronics & Communication Engineering with 7.5 years of related experience.

II. Languages

  • PL SQL

  • T-SQL

  • Python (Data/Analytics libraries)

  • Shell Scripting (bash, ksh)

III. Databases

  • Oracle

  • MSSQL

  • Snowflake

  • Postgres

  • MySQL

  • ElasticSearch

IV. BI / Reporting Tools

  • Power BI

  • Tableau

  • Oracle Business Intelligence Enterprise Edition (OBIEE)

  • Oracle BI Publisher (BIP)

  • Microstrategy

  • SQL Server Reporting Services (SSRS)

  • SQL Server Analysis Services (SSAS)

  • Google Data Studio

  • Metabase

V. ETL and Batch Processing Tools

  • Oracle Data Integrator (ODI)

  • SQL Server Integration Services (SSIS)

  • Airflow

  • Automic UC4

VI. Cloud & Containers

  • AWS

VII. Retail Products

  • Robling (Snowflake Retail Data Model)

  • Oracle Retail Analytics (RA)

  • Oracle Retail Data Warehouse (ROW)

  • Oracle Retail Merchandise Operations Management (MOM) Suite

  • Oracle Retail Store Inventory Management (SIM)

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