Data Scientist 3 (IT) 4P/367

4P Consulting

Birmingham, Alabama

JOB DETAILS
SKILLS
Algorithms, Amazon Web Services (AWS), Analysis Skills, Apache Hadoop, Apache Spark, Big Data, Business Analysis, Business Case, Business Model, Cloud Computing, Cross-Functional, Data Analysis, Data Science, Data Sets, Data Visualization, Decision Support, Demand Forecasting/Planning, Energy & Utilities, Forecasting, GCP (Good Clinical Practices), Leadership, Machine Learning, Manufacturing Data Management, Microsoft Windows Azure, Multitasking, Network Operations Center, Operational Audit, Operational Support, Power BI, Presentation/Verbal Skills, Python Programming/Scripting Language, R Programming Language, Regulations, Reporting Dashboards, Scientific Method, Smart Grid, Statistical Modeling, Statistical Programming Languages, Statistics, Systems Scalability, Tableau, Technical Presentation, Travel Industry, Travel Planning, Use Cases, Willing to Travel
LOCATION
Birmingham, Alabama
POSTED
30+ days ago

Data Scientist 3

Location: Birmingham, AL 35203 

Client- Alabama Power

Contract- 1 Year

Job Summary

We are seeking an experienced Data Scientist (Level 3) with 5–10 years of advanced data analytics experience to join our team. This role requires a strong foundation in statistics, machine learning, and data engineering. The successful candidate will leverage big data tools, programming expertise, and statistical modeling to develop insights and support critical decision-making in the utilities industry.

Key Responsibilities

  • Data Wrangling & Exploration

    • Acquire, clean, and process large, complex datasets from multiple sources, including smart meters, grid sensors, customer systems, and financial platforms.

    • Explore data for anomalies, trends, and correlations to support operational, engineering, and business use cases.

  • Model Development

    • Build, validate, and deploy machine learning and statistical models for applications such as predictive maintenance, outage prediction, customer load forecasting, and energy demand analysis.

    • Evaluate and apply appropriate ML algorithms including regression, classification, clustering, and time-series forecasting.

  • Visualization & Reporting

    • Develop intuitive data visualizations and dashboards using tools like Power BI, Tableau, or Python libraries (Matplotlib, Seaborn, Plotly).

    • Translate complex results into clear business insights for engineering, operations, and leadership teams.

  • Big Data & Advanced Analytics

    • Utilize big data frameworks such as Spark, Hadoop, or Databricks to process and analyze large-scale structured and unstructured datasets.

    • Support integration of analytics into operational systems, ensuring scalability and performance.

  • Collaboration

    • Partner with cross-functional stakeholders in grid operations, transmission, distribution, and customer solutions to identify high-value data science opportunities.

    • Work closely with data engineers, business analysts, and domain experts to align models with business and regulatory needs.

Experience:

    • 5–10 years of applied data science experience in an enterprise setting.

    • Proven success in designing, deploying, and scaling advanced analytics models.

    • Utilities or energy-sector experience strongly preferred (e.g., transmission, distribution, smart grid, AMI/MDM, renewable integration).

  • Technical Skills:

    • Proficient in Python or R (statistical programming).

    • Strong statistical knowledge and experience applying the scientific method.

    • Hands-on experience with machine learning frameworks (scikit-learn, TensorFlow, PyTorch).

    • Skilled in SQL and database querying.

    • Experience with big data tools (Spark, Hadoop, Databricks) is highly desirable.

    • Familiarity with cloud platforms (Azure, AWS, or GCP).

  • Soft Skills:

    • Strong problem-solving and analytical abilities.

    • Ability to present technical findings to non-technical stakeholders.

    • Self-motivated, with capacity to work independently and collaboratively.

Work Environment

  • Hybrid work arrangement with periodic travel to company sites, data centers, or field locations.

  • Must be able to balance multiple concurrent projects in a fast-paced, results-driven environment.

About the Company

4

4P Consulting