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Data Scientist, Marketing Strategy & Insights - Pleasanton California

Company: 10x Genomics, Inc.
Location: Pleasanton, California
Posted On: 11/13/2024

About the Role: At 10x Genomics, everything we do is driven by our mission: To accelerate the mastery of biology to advance human health. Our Marketing Strategy & Insights function is a cross-disciplinary team that plays a key role in developing insights on market opportunities and strategies for success. We build tools and frameworks to help make informed, data-driven decisions. We are committed to hiring the world's best and brightest people with knowledge and skill sets at the intersection of market research, marketing operations, data analytics, and data science. What you will be doing: This role will work cross-functionally to build the framework, underlying data structures, tools, and processes for measuring the effectiveness of our marketing and drive continuous improvement. The successful candidate will be responsible for providing data-driven insights such as building business cases, data modeling, and performance reporting. Initial responsibilities will include, but are not limited to:

  • Increase actionable insights and improve decision-making across the company by:
    • Contributing data science expertise to market research and market modeling efforts
    • Supporting Marketing teams by developing campaign attribution models to identify high impact campaigns
    • Supporting Product Management teams in building business cases for new product concepts
    • Leading internal marketing efforts to determine master data requirements and align across functions and systems to enable more efficient and robust reporting
    • Improving underlying processes and data structures for reporting
    • Identifying high impact channels and recommending the optimized channel mix
    • Drive continuous improvement in our marketing by:
      • Partnering with Marketing Analytics and Finance to define CAC and LTV, and building a framework to implement in reporting
      • Implementing A/B test frameworks and educating stakeholders across marketing to increase adoption
      • Modeling marketing mix and suggesting next best action on a personalized basis
      • Improving reporting tools that serve both executives and execution-oriented marketers Minimum Requirements:
        • BS in STEM or related field
        • Minimum 3 years' experience in a related role
        • Strong analytical skills
        • Advanced knowledge of R, SQL, Python (e.g., pandas, jupyter notebooks) for data manipulation
        • Applied statistics and machine learning experience (regression analysis, time series, probabilistic models, supervised and unsupervised methods)
        • Deep understanding of data architecture, pipelines, and enterprise systems
        • Experience with effective data visualization and reporting tools (i.e. Tableau, PowerBI) and open-source Python libraries (i.e. Plotly and Bokeh)
        • Proven ability to turn data analysis into actionable business insights and recommendations with quick turnaround times
        • Excellent problem-solving, project management, and communication skills.
        • Ability to interpret complex information and provide strategic recommendations in a simple and concise manner.
        • Demonstrated ability to work independently and manage multiple priorities in a fast-paced environment. Preferred Qualifications:
          • Experience with marketing operations and analytics for a multinational company as specified in "About the Role" (data structures for marketing systems, marketing mix, survey analysis)
          • Experience with Python application development frameworks (Flask, Django) and data app frameworks (Streamlit)
          • Experience using Generative AI models and frameworks e.g., ChatGPT, open source LLM, Langchain, Retrieval Augmented Generation (RAG)
          • Understanding of businesses financials and ability to articulate work in terms of contribution to financials and mission
          • BS/MBA in Finance, Accounting, Economics, Business Analytics (preferred both)
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