Advanced Analytics Architect I

Toyota Material Handling•Columbus, IN

2d•$115,419 - $130,350•Hybrid

About The Position

Toyota Material Handling, Inc. seeks an Advanced Analytics Architect I based in Columbus, IN to gather requirements by collaborating with business, data, and organizational leaders, to understand processes and their data needs, challenges, and opportunities. Design and implement end-to-end analytics solutions that automate decision-making processes. Identify and define analytics opportunities for the organization. Design technologies and solutions to address those opportunities. Assemble people, processes, and technology for data programs and projects. Develop ETL (Extract, Transform, and Load) pipelines for data preprocessing and integration from multiple sources. Organize and manipulate data from acquisition to DL/DW to presentation structures. Conduct descriptive, predictive, and prescriptive analysis to interpret complex data sets, uncover trends, and provide actionable insights. Create and present data visualizations and reports to communicate insights effectively to stakeholders. Explore advanced analytical solutions and implement demonstrations. Collaborate with cross-functional teams, including business analysts, data architect and software developers, to translate business requirements into technical solutions. Act as an expert advisor on data analytics to internal teams, ensuring best practices in development, deployment, and maintenance. Stay current with the latest trends, technologies, and advancements in the fields of data analytics, and machine learning. Propose and implement innovative approaches to solving complex business problems using data-driven methods. Support audit and data compliance procedures. Identify ways to improve data reliability, efficiency, and quality. Local telecommuting permitted 2 days per week.

Requirements

Requires a Master’s degree in Computer Science, Data Analytics, Business Administration--Information Systems, or a related field plus 2 years (or a Bachelor’s degree plus 5 progressive years) of analytics experience
Manipulating data with SQL, R and Python
Data management and data modeling, including creating database objects and working in notebooks
Data Integration and ETL frameworks and tools
Database systems and data warehousing solutions
Statistical analysis, predictive modeling, data mining techniques, and/or machine learning solutions
Visualization tools (Power BI) and data reporting
Experience with manipulating data with SQL and Python
Cloud (Azure) data services
Cloud data platform (Snowflake and Databricks)
Employer will accept experience gained before, during or after Master’s degree.
Employer will accept any suitable combination of education, training or experience.

Responsibilities

Gather requirements by collaborating with business, data, and organizational leaders, to understand processes and their data needs, challenges, and opportunities.
Design and implement end-to-end analytics solutions that automate decision-making processes.
Identify and define analytics opportunities for the organization.
Design technologies and solutions to address those opportunities.
Assemble people, processes, and technology for data programs and projects.
Develop ETL (Extract, Transform, and Load) pipelines for data preprocessing and integration from multiple sources.
Organize and manipulate data from acquisition to DL/DW to presentation structures.
Conduct descriptive, predictive, and prescriptive analysis to interpret complex data sets, uncover trends, and provide actionable insights.
Create and present data visualizations and reports to communicate insights effectively to stakeholders.
Explore advanced analytical solutions and implement demonstrations.
Collaborate with cross-functional teams, including business analysts, data architect and software developers, to translate business requirements into technical solutions.
Act as an expert advisor on data analytics to internal teams, ensuring best practices in development, deployment, and maintenance.
Stay current with the latest trends, technologies, and advancements in the fields of data analytics, and machine learning.
Propose and implement innovative approaches to solving complex business problems using data-driven methods.
Support audit and data compliance procedures.
Identify ways to improve data reliability, efficiency, and quality.