Manager, Business Analytics

Veracyte•San Diego, CA

11h•$131,562 - $146,378•Remote

About The Position

At Veracyte, we offer exciting career opportunities for those interested in joining a pioneering team that is committed to transforming cancer care for patients across the globe. Working at Veracyte enables our employees to not only make a meaningful impact on the lives of patients, but to also learn and grow within a purpose driven environment. This is what we call the Veracyte way – it’s about how we work together, guided by our values, to give clinicians the insights they need to help patients make life-changing decisions. Our Values: We Seek A Better Way: We pursue bold ideas, embrace complexity, and keep pushing forward. We Make It Happen: We act with urgency, deliver with excellence, and always find a way. We Are Stronger Together: We engage with empathy, align around what's best for Veracyte, and celebrate as one team. We Care Deeply: We show up with integrity, kindness, and respect for one another. The Position: The Manager, Business Analytics is a highly technical individual contributor within the Sales Operations & Business Analytics (SOBA) Center of Excellence. You will serve as a strategic analytics partner across Commercial, Operations, Finance, and other business functions, leveraging advanced analytics, statistical modeling, data science, and automation to improve operational performance, revenue realization, and business decision-making. The successful candidate combines deep technical expertise with strong business acumen, translating complex data into actionable insights that influence leadership decisions and drive measurable business outcomes. Working at the intersection of analytics, business intelligence, data engineering, and operational strategy, this individual partners closely with stakeholders across the enterprise to build scalable analytical solutions that enable data-driven decision-making.

Requirements

Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Systems, Analytics, or a related quantitative field.
6-8+ years of experience in advanced analytics, business intelligence, data science, revenue analytics, or a similar technical analytical role.
Expert-level SQL skills, including complex joins, window functions, common table expressions (CTEs), query optimization, and dimensional data modeling.
Strong Python programming experience, including the use of libraries such as Pandas, NumPy, SciPy, StatsModels, Scikit-Learn, and data visualization frameworks.
Strong understanding of data warehousing concepts, ETL/ELT processes, data governance, and data quality management practices, including cloud data platforms such as Snowflake, Redshift, Databricks, BigQuery, Azure Synapse, or similar technologies
Experience with Tableau, Power BI, or similar business intelligence platforms, including dashboard development and performance optimization.
Demonstrated ability to analyze large, complex datasets and communicate findings through compelling narratives, insights, and recommendations.
Ability to independently manage ambiguous problems and deliver high-impact solutions in a fast-paced environment.

Nice To Haves

Experience within diagnostics, laboratory services, healthcare technology, life sciences, or payer analytics environments.
Exposure to AI-enabled analytics, generative AI applications, workflow automation platforms, and emerging analytics technologies.
Experience partnering with executive stakeholders to influence strategic business decisions through data-driven insights.

Responsibilities

Serve as the analytics lead supporting Commercial, Finance, Operations, and related organizational functions.
Act as a thought partner to operational and commercial leadership, helping prioritize analytical investments, define success metrics, and measure business outcomes.
Collaborate cross-functionally to ensure analytical solutions are aligned with strategic priorities and deliver measurable value to the business.
Design, develop, and maintain scalable analytical solutions using SQL, Python, Snowflake, Tableau, Power BI, and modern cloud-based data platforms.
Perform statistical analysis, forecasting, segmentation, hypothesis testing, predictive modeling, and exploratory data analysis to support business planning and operational decision-making.
Partner with Data Engineering, IT, and Master Data Management teams to define data requirements, improve data quality, optimize data pipelines, and enhance enterprise data architecture.
Build and maintain semantic data models, reusable datasets, KPI frameworks, and standardized metrics aligned with SOBA governance standards.
Support enterprise data governance initiatives by validating source system integrity, documenting metric definitions, monitoring data quality, and promoting reporting consistency.
Leverage AI, machine learning, and advanced analytics techniques where appropriate to improve forecasting accuracy, automate decision support, and uncover new business insights.