Senior Data Science Analyst

CEI

Richmond (VA)

Hybrid

USD 90,000 - 130,000

Full time

14 days+

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Benefits offered by this job

Medical insurance

Vision insurance

401(k)

Job summary

A leading utility organization is seeking a Senior Data Science Analyst to support strategic initiatives. This role involves leading analytics projects, applying advanced machine learning, and collaborating across departments to optimize operational efficiency. Candidates should have strong communication skills and a background in big data analytics.

Qualifications

Minimum 5 years of hands-on experience as a data scientist.
Strong statistical modeling skills required.
Excellent communication and interpersonal skills needed.

Responsibilities

Lead and execute high-visibility data science projects.
Conduct exploratory data analysis and statistical modeling.
Translate complex data findings into clear recommendations.

Skills

Statistical modeling

Python

Machine learning

Predictive modeling

Data analysis

Big Data Ecosystem

Communication

Education

Bachelor’s degree in Computer Science, Information Systems, or Mathematics

Tools

Hadoop

HDFS

Spark

Jupyter

Zeppelin

Job description

This range is provided by CEI. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Information Technology Professional Recruiter

One of CEI's largest Energy, Power, & Electric Utilities clients is seeking a Sr. Data Science Analyst to join their growing organization!

Client/Industry: Energy, Power, & Electric Utilities

Job Title: Senior Data Science Analyst

Work Schedule: Alternating weekly schedule of 5 days onsite & 5 days remote | Minimum 40 work hours per week.

Duration/Length of Assignment: 12 Month Contract to Hire

Additional Information: Candidates will go through the process of obtaining an Export Control Clearance prior to start

*Must be able to convert to a full-time employee without sponsorship, restrictions, or an additional employer*

W2 Employment Only – No Corp to Corp / C2C arrangements.
Expected potential for contract extension(s) and/or conversion to Full-Time/Permanent Employment.
Optional benefits available during contract (Medical, Dental, Vision, and 401k)

Position Overview:

We are supporting a leading utility organization in the recruitment of two Senior Data Science Analysts to join an enterprise analytics group supporting company-wide strategic initiatives. These roles are being added as part of an effort to strengthen the company’s data-driven decision-making capabilities and optimize operational efficiency through advanced machine learning and predictive analytics. The position is part of a cross-functional analytics team composed of data scientists, engineers, and business stakeholders working collaboratively to deliver actionable insights for critical business functions. The environment supports independent project ownership while maintaining a strong peer-review culture and consistent team collaboration. In this position, the analyst will lead and execute high-visibility data science projects from end to end. This includes collecting business requirements, conducting exploratory data analysis, designing and testing machine learning models, and presenting insights to senior stakeholders. Candidates are expected to work across departments on multiple analytics initiatives and demonstrate strong autonomy in applying their data science skills to solve complex business problems. The role is highly collaborative, requiring clear communication, thoughtful documentation, and mentorship of junior analysts as needed.

Required Skills/Experience/Qualifications:

Bachelor’s degree or higher in Computer Science, Information Systems, or Mathematics
Minimum 5 years of hands-on experience working as a data scientist using R or Python on Hadoop platforms
Strong statistical modeling skills and advanced knowledge of R, Python, or both
Demonstrated ability to design and lead data science projects that solve business problems through machine learning
Practical expertise in predictive modeling, classification, regression, and clustering methodologies
Proven experience working with Big Data Ecosystems, including Hadoop, HDFS, Hive, Sqoop, Spark, PySpark, SparkR, SparkSQL, Jupyter, and Zeppelin notebooks
Proficient in working with both structured and unstructured datasets
Excellent communication skills, both written and verbal, with the ability to deliver presentations to business and technical audiences
Strong interpersonal skills and ability to work independently or in cross-functional teams

Preferred Skills (Not Required):

Experience or working knowledge of data engineering principles or frameworks
Familiarity with cloud technologies such as AWS, Azure, Google Cloud Platform (GCP), or Snowflake
Prior experience working in large-scale utility organizations or capital project environments

Day to Day/Responsibilities:

Work independently to lead analytics projects that span across departments and impact operational decisions
Conduct meetings with business stakeholders to gather analytic requirements and clarify project objectives
Perform feature engineering and exploratory data analysis on complex datasets, including both structured and unstructured formats
Apply statistical modeling and machine learning algorithms such as classification, regression, and clustering to address core business challenges
Use R, Python, and Jupyter/Zeppelin notebooks to develop, test, and document model prototypes
Work within a Hadoop-based big data environment, utilizing components such as Hive, Spark, SparkSQL, PySpark, and SparkR
Validate and compare performance metrics across multiple machine learning models to determine optimal solutions
Collaborate with data engineers when needed to build or improve data integration pipelines
Translate complex data findings into clear recommendations and present results to both technical and non-technical stakeholders
Guide or mentor less experienced analysts by providing technical direction and project support
Participate in code reviews, documentation, and peer collaboration to maintain high standards and team alignment
Balance multiple analytics projects simultaneously while adhering to business timelines and project scopes
Work alternating weekly schedules in a hybrid setup, maintaining presence during required onsite weeks in Richmond, VA

Seniority level