Machine Learning Data Scientist

Digital Prospectors • Contract • Pittsburgh, PA, US • 3d ago

Position: Machine Learning Data Scientist

Location: Pittsburg, PA (On-Site)

Length: 6 Month Contract to Start

* Please no agencies. Direct employees currently authorized to work in the United States – no sponsorship available.*

Job Description:

We are looking for a Data Scientist/Engineer with Machine Learning and strong skills in Python, time-series modeling, and SCADA/industrial data. In this role, you will build and deploy ML models for forecasting, anomaly detection, and predictive maintenance using high-frequency sensor and operational data.

Essential Duties and Responsibilities:

Develop ML models for time-series forecasting and anomaly detection
Build data pipelines for SCADA/IIoT data ingestion and processing
Perform feature engineering and signal analysis on time-series data
Deploy models in production using APIs, microservices, and MLOps best practices
Collaborate with data engineers and domain experts to improve data quality and model performance

Qualifications:

Strong Python skills
Experience working with SCADA systems or industrial data historians
Solid understanding of time-series analytics and signal processing
Experience with cloud platforms and containerization (AWS/Azure/GCP, Docker)

POST-OFFER BACKGROUND CHECK IS REQUIRED. Digital Prospectors is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law. Digital Prospectors affirms the right of all individuals to equal opportunity and prohibits any form of discrimination or harassment.

Come see why DPC has achieved:

4.9/5 Star Glassdoor rating and the only staffing company (< 1000 employees) to be voted in the national Top 10 ‘Employee’s Choice - Best Places to Work’ by Glassdoor.
Voted ‘Best Staffing Firm to Temp/Contract For’ seven times by Staffing Industry Analysts as well as a ‘Best Company to Work For’ by Forbes, Fortune and Inc. magazine.

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Job #18135