Data Scientist 3
Data Scientist 3
Posted on :
27-09-2024
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Job Description
ONLY W2 with benefits
Typical Day in the Role
- Purpose of the Team: The purpose of this team is working with the Mixed Reality Product Analytics team which develops data collection and processing systems to improve the product capabilities.
- Key projects: They will drive datadriven decisionmaking across product analytics and engineering processes. This individual will manage product analytics develop key performance metrics and ensure seamless integration of data systems and tools.
- Typical task breakdown and operating rhythm: The role will consist of :15% Meetings 20% reporting 65% heads down
- Daily Breakdown: 2030min Daily Team Sync
- First: Working with DRIs for release plans for HW equipment and gathering data off these testers helping monitor tester health
- Second: Gathering and plotting test data cumulating dashboards charts and trends and sharing them out
- Depending on the day: Utilizing SAS tools like JMP/PowerBI to helpfind trends in the data monitor process control and send out updates/make slide decks
- Finally: Tester support issues outages new feature requests more interrupt programming depending on what needs to be done.
Compelling Story & Candidate Value Proposition
Unique Selling Points: High Visibility/Impact Role
Candidate Requirements
- Years of Experience Required: 5 overall years of experience in the field.
- Degrees or certifications required: Bachelors degree in Data Science Statistics Computer Science or a related field is required to be eligible for this role.
- Disqualifiers: N/A
- Best vs. Average: The ideal resume would contain the ability to translate complex data insights into actionable recommendations excellent communication skills. Expertise in statistical analysis process control and engineering practices is essential for optimizing product quality and efficiency.
- Performance Indicators: Performance will be assessed based on accuracy and timeliness of product analytics reports successful integration of test stations into workflows improvement in yield rates and reduction of production errors. effective monitoring of CPK and PPK metrics.
Top 3 Hard Skills Required Years of Experience
- Minimum 5 years experience in data science or analytics with a focus on manufacturing or product engineering.
- Minimum 5 years experience with proficiency in Python R SQL and data visualization tools (JMP Power BI).
- Minimum 5 years experience with strong expertise in statistical analysis process control methodologies and data integration tools.
Hard Skills Assessments
- Expected Dates that Hard Skills Assessments will be scheduled: ASAP
- Hard Skills Assessment Process: The assessment process will include Panel with 3 people on the team 45mins1hr
- Required Candidate Preparation: Candidates should be prepared to talk about their previous work
Job Responsibilities:
- Product Analytics Management: Oversee all product analytics including data collection and reporting.
- Leverage data insights to enhance product quality performance and customer satisfaction.
- Station Greenlight and Release Processes: Participate in station greenlight and release plans providing datadriven recommendations.
- Collaborate with crossfunctional teams to ensure quality and performance standards are met prior to release.
- Process Control and Engineering Metrics: Develop CPK and PPK process control monitors for each tester ensuring alignment with engineering standards.
- Record and track tester performance identifying trends and areas for improvement.
- Integration of Testing in Factory Flow: Lead integration of test stations into factory workflows optimizing production and mapping testing to requirements.
- Oversee yield and error reporting providing insights to enhance production efficiency.
- Data Vetting and Integration: Manage the IPMR data vetting process to ensure data accuracy and integration into relevant systems for realtime decisionmaking.
- CTx Measurement Mapping and Traceability: Develop CTx measurement mapping for tracking key performance indicators throughout the product lifecycle.
Additional Responsibilities:
- Data Governance and Quality Assurance: Establish data governance standards ensuring accuracy and integrity across analytics processes.
- Collaboration and Communication: Work closely with engineering quality and production teams to align data strategies with organizational goals.
- Present findings to senior leadership translating complex data into actionable insights.
- Continuous Improvement: Identify opportunities for process optimization within the analytics framework.
- Stay current with emerging data science technologies to enhance decisionmaking capabilities.
Employment Type
Full Time
Key Skills
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