Manager of Data Analysis, Production Support

Important: This position will work in one of the following three Extended-Hours Support (ExHS) shift teams:

1. Weekend Shift Team
1a. Rotation 1: Sunday to Thursday (9AM–5PM), Friday and Saturday off
1b. Rotation 2: Tuesday to Saturday (9AM–5PM), Sunday and Monday off

2. Early-Morning Shift Team
2a. Rotation 1: Monday to Friday (4AM–12PM Pacific Time), Saturday and Sunday off
2b. Rotation 2: Tuesday to Saturday (4AM–12PM Pacific Time), Sunday and Monday off

3. Late-Evening Shift Team
3a. Rotation 1: Monday to Friday (3PM–11PM Pacific Time), Saturday and Sunday off
3b. Rotation 2: Sunday to Thursday (3PM–11PM Pacific Time), Friday and Saturday off

Important notes:

• During hiring, candidates will select and commit to one shift team (Weekend, Early-Morning, or Late-Evening).
• Once hired and onboarded, the team member will work exclusively within that shift team.
• ExHS team members rotate quarterly (every three months) between their team's two rotations.
• There are no rotations between shift teams.

The ideal person for this position is an experienced, hands-on data professional who has managed a team in a regulated lab or healthcare setting, is still comfortable writing SQL and Python, stays calm under pressure, communicates clearly with both technical and non-technical partners, with a strong sense of ownership for patient outcomes.

PRIMARY RESPONSIBILITIES:

Leadership

• Lead and mentor the specific ExHS shift team, fostering a culture of accountability, innovation, and collaboration.
• Measure, report, and continuously improve team operational effectiveness.
• Define and track team objectives, ensuring alignment with broader organizational goals.
• Provide career growth opportunities, feedback, and performance assessments for team members.
• Encourage individual contributors (ICs) to pitch ideas for process improvements and innovations.

Operational Excellence

• Ensure timely and accurate resolution of production escalations data analysis tickets.
• Train and coach team members on new technologies, procedures, and guidelines/best practices.
• Enforce operating procedures for compliance, quality, and efficiency.
• Manage and improve tracking systems for workload, capacity, and ticket SLAs.

Communication and Collaboration

• Represent the Extended-Hours Support (ExHS) teams in stakeholder meetings.
• Proactively manage stakeholder expectations.
• Establish regular stakeholder reporting mechanisms.
• Translate complex analytical results into actionable recommendations for cross-functional partners.
• Effectively and correctly escalate issues encountered to other DSPE teams.

Process Improvement and Innovation

• Identify opportunities for automation and process enhancements to streamline operations.
• Identify and escalate risks such as data model changes that impact project timelines or ticket TAT.
• Collaborate with the overall DSPE team to develop new and improve existing support solutions.

QUALIFICATIONS:

• Master's degree in a related field (e.g., Statistics, Data Science, Computer Science).
• Minimum 5 years of working experience in a highly regulated environment, e.g., CLIA and/or FDA compliant settings.
• Minimum 5 years of hands-on experience in data analysis and/or statistical modeling in data production, data engineering, data analytics, analytics production support roles.
• Minimum 2 years in a team management role.
• Knowledge of regulatory requirements, such as HIPAA and FDA guidelines.
• Working knowledge of the business processes and requirements of diagnostic laboratories.
• Proven track record in managing production escalations, data workflows, and team operations.
• Experience with healthcare data, and clinical terminology is a plus.
• Functional understanding of next-gen sequencing workflows.

KNOWLEDGE, SKILLS, AND ABILITIES:

• Proficient in data analysis and statistical techniques.
• Proficient in Python and SQL development.
• Working knowledge of Snowflake platform technologies.
• Strong SQL skills for querying and retrieving data from complex data sources in a structured format.
• Strong understanding of various statistical concepts (parametric & non-parametric distributions, hypothesis testing, probability, regression).
• Proficient in aggregating data, preparing, cleaning data, and data mining using SQL and Python.
• Familiarity with machine learning techniques and their practical applications in real-world datasets.
• Strong leadership and team management skills.
• Excellent problem-solving and critical-thinking abilities.
• Good documentation practices and coding style.
• Strong verbal and written communication skills, with the ability to present technical findings to both technical and non-technical audiences.
• Experience using version control systems such as GitHub or GitLab for managing code and collaboration.
• Attention to detail and a commitment to data accuracy.
• Ability to work collaboratively in a cross-functional team environment.
• Strong integrity.