10x Genomics
StaffDataScientist,CommercialAnalytics
Neural analysis suggests this role is
optimal for Senior candidates.
“Staff Data Scientist, Commercial Analytics at 10x Genomics. Skills: Commercial Analytics, Predictive Signal Modelling, Stakeholder Partnership, Production ML Experience, SQL, Python, R, Tableau, Power BI, Salesforce. Conduct deep-dive analyses on quota attainment, territory performance, and account penetration, segmenting by geography, account type, product line, and sales rep tenure.. Conduct deep customer analyses that map account health, buying patterns, and product adoption across segments t”
What You'll Achieve.
Design specific performance frameworks for distributor-led markets (APACEA), creating proxy metrics to measure success where we do not own the "last mile" of customer data.; map account health, buying patterns, and product adoption across segments translating behavioral signals from Salesforce and analytical tool usage into a clear view of whitespace, risk, and untapped expansion potential.; predict customer expansion and system utilization.; define the "scientific floor" for global discounting.; integrated directly into our CPQ (Configure, Price, Quote) workflows or regional sales guidelines.; maximizing gross margin while maintaining a competitive win rate.; giving field teams actionable signals weeks before issues surface in lagging indicators.; capture behavioral signals that precede customer disengagement or expansion.; integrating outputs directly int Salesforce workflows so reps act on insights without leaving their existing tools.; directly influence commercial strategy and business growth through data-driven insights.
Industry & Context.
solve complex business problems; translate ambiguous business questions into structured analytical problems
What They're Looking For.
Must Have
Master’s degree in a quantitative discipline such as Statistics, Engineering, Mathematics, Computer Science, Data Science, or an MBA with a technical focus., 7+ years of experience using analytics to solve complex business problems, including coding (Python or R), querying databases (SQL), and statistical analysis., Production ML Experience: Proven track record of deploying machine learning models into production environments to solve commercial or operational challenges., Expert-level proficiency in writing complex, efficient SQL and using Python/R for data manipulation and predictive modeling., Profound experience with sales processes and tools, specifically Salesforce CRM, sales quota/territory assignment, and the B2B enterprise SaaS demand generation funnel., Advanced knowledge of data visualization tools like Tableau or Power BI to synthesize data into actionable executive dashboards., Exceptional communication and interpersonal skills, with the ability to lead through ambiguity and influence cross-functional teams.
Nice to Have
9+ years of experience in data science or commercial analytics within a high-growth environment., Experience with Machine Learning Operations (MLOps) tools and practices to maintain model health and scalability., Experience working within a healthcare, life sciences multinational, or a leading tech-driven organization., Proven ability to conduct technology assessments and ROI analysis for complex organizational system solutions.
What You'll Do.
Conduct deep-dive analyses on quota attainment
territory performance
and account penetration
segmenting by geography
and sales rep tenure.
Conduct deep customer analyses that map account health
and product adoption across segments translating behavioral signals from Salesforce and analytical tool usage into a clear view of whitespace
and untapped expansion potential.
Act as the commercial "voice of the data" to our Product and Software Engineering teams.
Strategize what telemetry we need to collect from our instruments and software to better predict customer expansion and system utilization.
Develop and maintain price elasticity models that define the "scientific floor" for global discounting.
Translate these models into actionable pricing guardrails that are integrated directly into our CPQ (Configure
Quote) workflows or regional sales guidelines.
Analyze historical discounting patterns across regions and account types (Academic vs. Pharma) to identify where we are leaving money on the table.
Ensure we are maximizing gross margin while maintaining a competitive win rate.
Build and own early-warning models that detect churn risk
and expansion readiness at the account level giving field teams actionable signals weeks before issues surface in lagging indicators.
Develop feature sets from disparate sources such as Salesforce activity
analytical tool usage patterns
and field notes to capture behavioral signals that precede customer disengagement or expansion.
Establish a signal monitoring framework that automatically flags at-risk and high-opportunity accounts
integrating outputs directly int Salesforce workflows so reps act on insights without leaving their existing tools.
Translate ambiguous business questions into structured analytical problems.
Communicate findings in plain language without hiding behind technical complexity.
Mentor junior analysts on the team.
Raise the technical bar for the team.
How You'll Work.
Team & Collaboration
alert stakeholders when model drift requires recalibration.; Act as the commercial "voice of the data" to our Product and Software Engineering teams.; influence cross-functional teams.
Communication Scope
Exceptional communication and interpersonal skills; communicate findings in plain language without hiding behind technical complexity
Full Job Description
About the Position 10x Genomics sells high-complexity capital equipment and consumables into academic research institutions, biotech companies, and large pharma. Our commercial ecosystem involves long sales cycles, regional field teams, and a global distribution network which means forecasting and territory analytics here are genuinely hard and genuinely consequential. We’re hiring a Senior Data Scientist to own the commercial analytics function within our Business Insights alert stakeholders when model drift requires recalibration. Design specific performance frameworks for distributor-led markets (APAC/EMEA), creating proxy metrics to measure success where we do not own the "last mile" of customer data. Commercial Analytics Conduct deep-dive analyses on quota attainment, territory performance, and account penetration, segmenting by geography, account type, product line, and sales rep tenure. Conduct deep customer analyses that map account health, buying patterns, and product adoption across segments translating behavioral signals from Salesforce and analytical tool usage into a clear view of whitespace, risk, and untapped expansion potential. Act as the commercial "voice of the data" to our Product and Software Engineering teams. You won't just analyze what we have; you will strategize what telemetry we need to collect from our instruments and software to better predict customer expansion and system utilization. Develop and maintain price elasticity models that define the "scientific floor" for global discounting. You will translate these models into actionable pricing guardrails that are integrated directly into our CPQ (Configure, Price, Quote) workflows or regional sales guidelines. Analyze historical discounting patterns across regions and account types (Academic vs. Pharma) to identify where we are leaving money on the table. You will ensure we are maximizing gross margin while maintaining a competitive win rate. Predictive Signal Modelling Build and own earl
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