Data Scientist — Predictive Analytics & ML

V15P1Talonnn; Chicago (IL); On-site; USD 30,000 - 40,000; Full time

Job summary

ADP is seeking a Data Scientist to analyze large datasets and develop predictive models that inform business strategies. You will work with cross-functional teams to uncover data-driven insights, design experiments, and communicate findings to stakeholders for actionable outcomes.

The role emphasizes staying current with advances in data science and machine learning, leveraging R and Python, and applying techniques like random forests, neural networks, and logistic regression.

Qualifications

• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field
• 3+ years of experience in data science or a related field
• Strong programming skills in R and Python
• Experience with machine learning techniques such as random forest, neural networks, and logistic regression
• Experience with statistical analysis and experimental design

Responsibilities

• Analyze large and complex data sets using statistical and machine learning techniques to develop predictive models
• Collaborate with cross-functional teams to identify opportunities for data-driven insights and develop solutions to improve business performance
• Design and implement experiments to test hypotheses and validate models
• Communicate findings and recommendations to stakeholders in a clear and concise manner
• Stay up-to-date with the latest developments in data science and machine learning to continuously improve our analytical capabilities

Skills

R

Python

ML techniques

Statistical analysis

Experimental design

Spark

TensorFlow

Data visualization

Education

Bachelor's degree in Computer Science/Statistics/Math

Tools

Apache Spark

TensorFlow

Job description

ADP is seeking a Data Scientist to analyze large datasets and develop predictive models that inform business strategies. You will work with cross-functional teams to uncover data-driven insights, design experiments, and communicate findings to stakeholders for actionable outcomes.

The role emphasizes staying current with advances in data science and machine learning, leveraging R and Python, and applying techniques like random forests, neural networks, and logistic regression.