Lead Data Scientist, Analytics & AI for Utilities

US101 Guidehouse Inc.

Atlanta (GA)

On-site

USD 90,000 - 130,000

Full time

2 days ago
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Benefits offered by this job

Medical Insurance
Dental Insurance
Vision Insurance
Sick Time & Holidays
Bonus Eligible
Parental Leave
401(k) Plan
Life Insurance
HSA/FSA
Disability Insurance
Student Loan Paydown
Tuition Reimbursement
Learning Opportunities
Certifications
Employee Referral
Community Events
Emergency Childcare
Mobility Stipend

Job summary

Guidehouse is seeking a data analytics professional to perform data analysis and build analytical solutions using Python, SQL, R, and BI tools such as Power BI and Tableau for utility clients in a consulting setting.

The role involves translating business needs into scalable data workflows, dashboards, and decision-support tools, mentoring analysts, and presenting findings to both technical and non-technical audiences.

Qualifications

  • Bachelor's degree and 3+ years of experience applying data analytics, BI or data science to solve business problems.
  • Proficiency with analytics and data management tools such as Python, SQL, R, Databricks, Power BI, Tableau, GIS, or similar technologies.

Responsibilities

  • Perform data analysis and develop analytical solutions to address client business challenges.
  • Partner with utility clients and subject matter experts to define objectives, approaches, requirements, and actionable recommendations.
  • Design, develop, test, and implement data and AI-enabled solutions that support client objectives.

Skills

Python
SQL
R
Databricks
Power BI
Tableau
GIS

Education

Bachelor's degree

Tools

Snowflake
Databricks

Job description

Guidehouse is seeking a data analytics professional to perform data analysis and build analytical solutions using Python, SQL, R, and BI tools such as Power BI and Tableau for utility clients in a consulting setting.

The role involves translating business needs into scalable data workflows, dashboards, and decision-support tools, mentoring analysts, and presenting findings to both technical and non-technical audiences.

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