Senior Data Scientist

job summary: Step into a pivotal role with a premier smart utility technology innovator, where your expertise in machine learning and data science will directly impact global resource conservation and operational efficiency. We are seeking a Senior Data Scientist to architect and deploy predictive AI solutions that process massive streams of IoT sensor data. If you are passionate about building scalable ML pipelines, evaluating model quality in production, and transforming complex data into actionable intelligence, this is your opportunity to drive meaningful change. We offer a comprehensive benefits package including medical, dental, and vision coverage.

location: Duluth, Georgia job type: Permanent salary: $120,000 - 140,000 per year work hours: 9am to 5pm education: Masters

responsibilities:

• Start your day by collaborating with product management and engineering teams to define, refine, and translate business requirements into robust AI-powered platform features.
• Dive into massive streams of IoT data to build and optimize efficient data processing workflows using PySpark and distributed computing frameworks.
• Design, train, and validate predictive machine learning models focusing on time-series analysis, anomaly detection, resource consumption forecasting, and predictive maintenance.
• Deploy production-ready machine learning pipelines to cloud infrastructure, utilizing advanced MLOps practices to orchestrate end-to-end workflows.
• Develop visually engaging analytics dashboards and write clean Python code to translate complex data insights for cross-functional stakeholders.
• Monitor the performance of production ML systems, performing continuous feature engineering and model selection to ensure peak operational accuracy.
• Spend time mentoring junior data scientists, reviewing code implementations, and shaping the overarching AI strategy for the organization in an Agile environment.

qualifications: Must-Haves

Master's or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field (or a Bachelor's degree with equivalent demonstrated experience).

5 or more years of hands-on professional experience in data science, machine learning, or advanced analytical roles.

5 or more years of programming experience using Python and core data libraries, including pandas, NumPy, scikit-learn, and TensorFlow or PyTorch.

Proven expertise writing complex SQL queries and interacting with large-scale relational databases (e.g., Redshift, PostgreSQL, MySQL).

Demonstrated success deploying machine learning models into production and a deep understanding of MLOps lifecycle management.

Strong background working with cloud platforms, specifically deploying architecture within the AWS ecosystem (SageMaker, Lambda, S3, Redshift).

Extensive experience analyzing time-series data and applying advanced forecasting methodologies.

Nice-to-Haves

Familiarity with big data AWS services such as Glue, EMR, and Athena.

Previous experience processing large-scale IoT data, vector databases, or working within industrial utility management operations.

Exposure to generative AI integrations, foundational large language models (like AWS Bedrock), and AI agents.

Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

At Randstad Digital, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact HRsupport@randstadusa.com.

Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad Digital offers a comprehensive benefits package, including: medical, prescription, dental, vision, AD&D, and life insurance offerings, short-term disability, and a 401K plan (all benefits are based on eligibility).

This posting is open for thirty (30) days.

,

• Start your day by collaborating with product management and engineering teams to define, refine, and translate business requirements into robust AI-powered platform features.
• Dive into massive streams of IoT data to build and optimize efficient data processing workflows using PySpark and distributed computing frameworks.
• Design, train, and validate predictive machine learning models focusing on time-series analysis, anomaly detection, resource consumption forecasting, and predictive maintenance.
• Deploy production-ready machine learning pipelines to cloud infrastructure, utilizing advanced MLOps practices to orchestrate end-to-end workflows.
• Develop visually engaging analytics dashboards and write clean Python code to translate complex data insights for cross-functional stakeholders.
• Monitor the performance of production ML systems, performing continuous feature engineering and model selection to ensure peak operational accuracy.
• Spend time mentoring junior data scientists, reviewing code implementations, and shaping the overarching AI strategy for the organization in an Agile environment.

Must-Haves Master's or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field (or a Bachelor's degree with equivalent demonstrated experience). 5 or more years of hands-on professional experience in data science, machine learning, or advanced analytical roles. 5 or more years of programming experience using Python and core data libraries, including pandas, NumPy, scikit-learn, and TensorFlow or PyTorch. Proven expertise writing complex SQL queries and interacting with large-scale relational databases (e.g., Redshift, PostgreSQL, MySQL). Demonstrated success deploying machine learning models into production and a deep understanding of MLOps lifecycle management. Strong background working with cloud platforms, specifically deploying architecture within the AWS ecosystem (SageMaker, Lambda, S3, Redshift). Extensive experience analyzing time-series data and applying advanced forecasting methodologies. Nice-to-Haves Familiarity with big data AWS services such as Glue, EMR, and Athena. Previous experience processing large-scale IoT data, vector databases, or working within industrial utility management operations. Exposure to generative AI integrations, foundational large language models (like AWS Bedrock), and AI agents.

Step into a pivotal role with a premier smart utility technology innovator, where your expertise in machine learning and data science will directly impact global resource conservation and operational efficiency. We are seeking a Senior Data Scientist to architect and deploy predictive AI solutions that process massive streams of IoT sensor data. If you are passionate about building scalable ML pipelines, evaluating model quality in production, and transforming complex data into actionable intelligence, this is your opportunity to drive meaningful change. We offer a comprehensive benefits package including medical, dental, and vision coverage.