Suggested rewrite: Led a cross-functional initiative that improved [business outcome] by [measurable result], demonstrating experience relevant to this role...
Manager, Business Analytics
- Remote from
- USA
- Salary
- USD 130k–145k / yr
- Department
- Data Science & Analytics
- Employment
- Full Time
- Experience
- Director
- Published
- Apply before
- 12 Dec 2026
- Listing views
- 29
- Application actions
- 0
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About this role.
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.
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.
Who You Are:
Required Qualifications:
- 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.
Preferred Qualifications:
- 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.
#LI-Remote
The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to years of experience, skillset, geographic location, industry, education, etc. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.
Pay range
$130,000—$145,000 USD
What We Can Offer You
Veracyte is a growing company that offers significant career opportunities if you are curious, driven, patient-oriented and aspire to help us build a great company. We offer competitive compensation and benefits, and are committed to fostering an inclusive workforce, where diverse backgrounds are represented, engaged, and empowered to drive innovative ideas and decisions. We are thrilled to be recognized as a 2024 Certified™ Great Place to Work® in both the US and Israel – a testament to our dynamic, inclusive, and inspiring workplace where passion meets purpose.
About Veracyte
Veracyte (Nasdaq: VCYT) is a global diagnostics company whose vision is to transform cancer care for patients all over the world. We empower clinicians with the high-value insights they need to guide and assure patients at pivotal moments in the race to diagnose and treat cancer. Our Veracyte Diagnostics Platform delivers high-performing cancer tests that are fueled by broad genomic and clinical data, deep bioinformatic and AI capabilities, and a powerful evidence-generation engine, which ultimately drives durable reimbursement and guideline inclusion for our tests, along with new insights to support continued innovation and pipeline development. For more information, please visit www.veracyte.com or follow us on LinkedIn or X (Twitter).
Veracyte, Inc. is an Equal Opportunity Employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability status. Veracyte participates in E-Verify in the United States. View our CCPA Disclosure Notice
If you receive any suspicious alerts or communications through LinkedIn or other online job sites for any position at Veracyte, please exercise caution and promptly report any concerns to careers@veracyte.com
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Core skills
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Sample interview questions
I use SQL to extract, join, and validate large datasets close to the warehouse, then use Python for analysis, statistical testing, forecasting, or automation. I document assumptions, reconcile outputs to source systems, and present the result through a dashboard or concise stakeholder narrative tied to a measurable business decision.
I would begin with stakeholder workshops to define business decisions and metric ownership. I would document calculation logic, source systems, grain, refresh cadence, and exceptions, then implement governed semantic models and reusable datasets. Finally, I would establish data-quality checks and a change-management process to keep definitions consistent.
I first establish a baseline forecast and identify the drivers of error by segment, time period, and data source. I test relevant features, compare interpretable statistical models with machine learning approaches where appropriate, and validate performance using time-based holdouts. I also ensure that the forecast can be operationalized and understood by business users.
I clarify the decision to be made, the desired outcome, the timeline, and the acceptable level of uncertainty. I propose a structured analytical approach with early checkpoints, communicate trade-offs clearly, and deliver an initial decision-ready insight before expanding the work into a scalable solution if needed.
I would define trusted source tables, implement automated validation checks, monitor freshness and completeness, and reconcile critical KPIs against finance or operational systems. I would also use version-controlled transformation logic, clear metric documentation, role-based access controls, and performance testing for high-use dashboards.
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