Data Scientist

Oxford Global Resources

Milwaukee, WI, United States

5 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Compensation

$43,680.0 - $58,240.0

Working hours

Regular working hours

Job source

www.jofdav.com

Tech stack

Amazon Web Services Microsoft Azure Big Data Cloud Computing Data Governance Data Integrity Data Visualization Database Queries Apache Hadoop Python (Programming Language) Machine Learning NumPy

+12 more

Power BI Software Tools Tableau (Software) Unstructured Data Data Processing Google Cloud Apache Spark Pandas Matplotlib Data Analytics Non-relational Database Data Pipelines

Job description

Analyze large volumes of structured and unstructured data to uncover patterns, trends, and actionable insights that support business decision-making.
Develop predictive models and machine learning algorithms to solve complex business problems and improve operational efficiency.
Design and implement data pipelines for data collection, cleaning, transformation, and storage using modern data engineering tools.
Create compelling data visualizations and dashboards to communicate findings to technical and non-technical stakeholders.
Collaborate with cross-functional teams to define data requirements, validate hypotheses, and deliver data-driven solutions aligned with strategic goals.
Ensure data integrity, privacy, and compliance with relevant regulations and industry standards.
Maintain comprehensive documentation for data sources, modeling approaches, and analytical processes.
Stay current with industry trends, emerging technologies, and best practices in data science and analytics. Proactively identify opportunities for innovation and optimization.

Requirements

5+ years’ experience in data science, analytics, or a related field with a strong understanding of statistical methods and machine learning techniques.
Proficiency in programming languages such as Python or R, and experience with data manipulation libraries (e.g., pandas, NumPy).
Strong SQL skills and experience working with relational and non-relational databases.
Experience with data visualization tools such as Tableau, Power BI, or matplotlib/seaborn.
Familiarity with cloud platforms (AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop).
Excellent communication skills with the ability to present complex data insights clearly and effectively.
Experience working in cross-functional teams and translating business needs into analytical solutions.
Knowledge of data governance, privacy regulations (e.g., GDPR), and ethical AI practices.