Staff Data Scientist - Growth
New
T
TwilioSaaS
Remote - USFull-TimeStaff
Salary155,520 - 194,400 USD per year
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Job Details
- Experience
- 7+ years
- Required Skills
- PythonSQLMachine LearningPyTorchAirflowSparkTensorflowA/B testingdbtRscikit-learnGenerative AI
Requirements
- 7+ years in Data Science/ML, with a proven track record in a GTM or Growth environment (SaaS experience preferred)
- 5+ years of experience with Applied Statistics/Machine Learning or experimentation (i.e. A/B testing) in an industry setting
- Expert-level proficiency in Python/R, SQL, and modern ML frameworks (Scikit-learn, XGBoost, PyTorch, or TensorFlow)
- Experience deploying models into production environments and building scalable data pipelines (Airflow, dbt, Spark)
- Experience initiating and driving projects which leverage Generative AI capabilities to drive productivity and efficiency, preferably in a product or technology organization
- Strong understanding of GTM metrics: CAC, LTV, ARR, ARPU, Pipeline Velocity, Lead-to-Close ratios, etc.
- Ability to explain a gradient-boosted tree to a Sales Director and a business strategy to a Data Engineer with equal clarity
- A degree in a quantitative field (e.g. statistics, mathematics, physics, econometrics, or computer science)
- Masters preferred but not required
- 5+ years of experience doing quantitative analysis at a technology company, consulting firm, investment bank, or product management firm
Responsibilities
- Translate business objectives into a data science roadmap that prioritizes high-LTV (Lifetime Value) growth
- Dig into the science of our self-service funnel and graduation to Sales to uncover optimization opportunities, diagnose issues, and provide actionable recommendations through data products
- Identify leading indicators of revenue and build data science models that surface high potential opportunities
- Serve as a key technical advisor to GTM leadership across Sales and Marketing
- Build extensive knowledge of user behavior, the customer purchase and usage experience, and our lead funnel to inform data science solutions
- Develop sophisticated recommendation engines that identify "next-best-action" opportunities within our existing customer base, ensuring sales and marketing engagement the right person at the right time
- Build robust frameworks to measure the incremental impact of your data products, moving beyond simple correlation to prove true ROI
- Leverage machine learning and generative AI capabilities to support Product-led-growth (PLG) initiatives
- Partner with Data Engineering to define the long-term roadmap for GTM data architecture, ensuring high-fidelity 'source of truth' data for signals like product-qualified leads (PQLs)
- Oversee the seamless integration of data products into the daily workflows of stakeholders, ensuring insights are delivered where they work (Slack, CRM, Wiki/Docs, Tableau, email, etc.)
- Create documentation, dashboards, reports, and executive summaries for your data products
- Partner with Sales, Marketing, Enterprise Technology, Product, and Ops teams to bring relevant data science products to life
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