Statistical Data Analyst

at  Olympus Corporation of the Americas

Workplace Flexibility: Field
Are you looking for a company that cares about people’s lives and health, including yours? Let’s inspire healthier lives, together.

JOB DESCRIPTION

We are looking for a Data Analyst / Data Engineer to Join Olympus’ Quality Assurance Continuous Improvement team. This role will be a good fit for someone with a passion for data and data visualization to help analyze system data and find actionable trends. This role will include statistical process control, capability analysis, big data analysis, data visualization and machine learning responsibilities across our development and product assurance teams.

ABOUT US:

Our Medical business uses innovative capabilities in medical technology, therapeutic intervention, and precision manufacturing to help healthcare professionals deliver diagnostic, therapeutic, and minimally invasive procedures to improve clinical outcomes, reduce costs, and enhance the quality of life for patients and their safety.
Headquartered in Tokyo, Japan, Olympus employs more than 31,000 employees worldwide in nearly 40 countries and regions. Olympus Corporation of the Americas, a wholly owned subsidiary of Olympus Corporation, is headquartered in Center Valley, Pennsylvania, USA, and employs more than 5,200 employees throughout locations in North and South America. For more information, visit www.olympusamerica.com.

OUR PURPOSE IS TO MAKE PEOPLE’S LIVES HEALTHIER, SAFER, AND MORE FULFILLING.

Our Core Values are reflected in all we do: Integrity – Empathy – Agility – Unity – Long-Term View
We deliver on our purpose and our core values by staying True to Life.
**Please note: All correspondence will be sent from our Olympus domain (@Olympus.com). If you receive correspondence from an entity other than @Olympus.com, it is likely not legitimate.

JOB DUTIES

• Navigate large complex datasets to produce descriptive analysis, correlations, and insights.
• Design, develop and optimize effective machine learning models.
• Conduct ad-hoc data analysis and innovation around data visualization.
• Work closely with stakeholders to understand business goals and priorities, and the role data plays in achieving them.
• Identify gaps in existing data collections and proactively work to fill them.
• Present analyses and recommendations to cross functional stakeholders for decision making in presentation.
• Analyzing data and present data through reports that aid decision-making.
• Recommend ways to improve data reliability, efficiency, and quality.
• Understanding what our customers need to create visual outputs, help the data engineers onsite understand what needs to be done to get from data collection to visual output.
• Data modeling and creating dashboards, wrangle data to make visual tools, and clean data in a way to facilitate data analytics.