Data Science Engineer / Data scientist

Hybrid in Easton, PA, US • Posted 10 hours ago • Updated 10 hours ago

Contract W2

50% Travel Required

On-site

$65 - $70/hr

Fitment

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Job Details

Skills

Manufacturing
OPC
Modbus
Spark
Kafka
Python

Summary

Title / Designation – Data Science Engineer / Data scientist

Experience Required Overall: 8-10 years

Domain Experience – Manufacturing 4-5 Years

Duration- 12 months + Extension possible

Base Location - Easton, Pennsylvania

Work Model – Onsite – Hybrid who are local or willing to relocate / Remote with travel across USA also is an option

Client Interviews - 2 (1 Technical & 1 Functional Cultural fit)

Mode of Interviews – Virtual

Job Description:

8–10 years of overall data science experience required along with 4-5 years working in manufacturing domain.
Hands-on experience in shop floor operations, production planning, and systems including MES, SCADA, and ERP.
Proficient in industrial protocols (OPC-UA, MQTT, Modbus) with ability to bridge OT/IT systems for real-time data extraction.
Applied experience with OEE, Six Sigma, SPC, and lean methodologies to drive measurable gains in yield, uptime, and efficiency.
Data Engineering Skilled in building scalable cloud data pipelines for high-volume manufacturing and IoT data using Spark, Kafka, Airflow, and Delta Lake.
Strong SQL and Python proficiency with hands-on experience in medallion/lakehouse architectures on Databricks, Snowflake, AWS, or Azure.
Data Science Proven track record building and deploying ML models for predictive maintenance, anomaly detection, demand forecasting, and root cause analysis.
Proficient in scikit-learn, TensorFlow, or PyTorch with experience moving models from prototype to production in industrial environments.
Strong communicator — able to translate complex model outputs into clear, actionable recommendations for operations and executive stakeholders.
Solid grounding in statistical methods — time series, regression, clustering, and hypothesis testing applied to manufacturing quality problems.
Experience designing A/B experiments and simulations to validate process changes and quantify business impact before full deployment.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 10305143
Position Id: 8916809
Posted 10 hours ago

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