Data Scientist (hybrid onsite)
The Data Scientist role at Confidential Client supports a leading manufacturing company by transforming complex data into actionable insights that drive operational improvements and business growth. This hybrid position involves building predictive models, automating data workflows, integrating analytics into enterprise systems, and communicating findings to diverse stakeholders to enhance forecasting accuracy and decision-making across departments.
About CareerTakes
CareerTakes is a next-generation AI recruiting platform that partners with leading organizations to connect job seekers with meaningful, high-impact roles.
👉 Important disclosure: CareerTakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client.
About the Opportunity
CareerTakes is sourcing on behalf of a confidential client in the manufacturing industry seeking a Data Scientist to transform complex organizational data into insights that drive smarter business decisions.
This role sits within the company’s Data Systems team, where you’ll work closely with engineers, analysts, and business leaders to develop predictive models, improve forecasting, and enhance operational performance across the organization.
The position follows a hybrid work schedule, allowing flexibility between the Buena Park and Riverside offices.
Work Model
Hybrid schedule with the following options:
- 3 days on-site in Buena Park, 1 day in Riverside, 1 day remote, or
- 3 days on-site in Riverside, 1 day in Buena Park, 1 day remote
What You’ll Do
Data Analysis & Modeling
- Analyze large and complex datasets to uncover trends, correlations, and opportunities for operational improvement
- Develop predictive models and machine learning algorithms to support forecasting and performance optimization
- Design statistical models to improve production efficiency, resource planning, and lead time management
Data Integration & Automation
- Collaborate with engineering teams to integrate predictive models into ERP, CRM, and business intelligence systems
- Automate data workflows and model updates to enable real-time insights
- Contribute to building unified data pipelines that support advanced analytics across the organization
Visualization & Communication
- Translate technical analyses into clear insights and dashboards using Power BI or similar tools
- Partner with teams across operations, sales, finance, and HR to support data-driven decision making
- Present findings and recommendations to both technical and non-technical stakeholders
Continuous Improvement
- Research emerging AI, machine learning, and automation technologies to improve business intelligence capabilities
- Monitor model performance and refine approaches to improve predictive accuracy
- Support the growth of data literacy across the organization through documentation and knowledge sharing
What We’re Looking For
- Bachelor’s degree in Data Science, Statistics, Computer Science, or related field
- 4+ years of experience in data modeling, analytics, or predictive analysis
Strong experience with SQL and Power BI or similar data visualization tools - Knowledge of statistical modeling, machine learning, and data visualization techniques
- Familiarity with ERP data structures and Microsoft 365 data tools (Power Automate, Copilot, Excel)
- Strong analytical thinking and the ability to translate complex data into actionable insights
Preferred
- Master’s degree in a related field
- Experience working with manufacturing or operational data environments
Compensation
Estimated compensation up to $60 per hour (W2) depending on experience, skills, and qualifications.
Equal Opportunity & Hiring Transparency
CareerTakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind.
To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.