Data Scientist II, Growth Marketing
Data Scientist II, Growth Marketing
Job Description
Responsibilities
- Lead the design, implementation, and continuous improvement of advanced marketing measurement frameworks and statistical models to quantify marketing ROI across channels like paid media, organic social, email, events, webinars, and elearning
- Build and deploy statistical and machine learning models such as propensity, forecasting, and lifetime value (LTV) models to optimize marketing strategies and enhance audience targeting
- Develop and refine attribution methodologies to evaluate the effectiveness of marketing initiatives across multiple channels
- Assess the incremental impact of marketing activities using causal inference techniques and testing/experiment frameworks
- Conduct deep, strategic analyses to address key business questions, such as improving marketing ROI, optimizing marketing budget allocation, measuring marketing impact in mature and new markets, and identifying opportunities to increase advertiser growth and revenue
- Translate complex analytical findings into clear, actionable insights and strategic recommendations for both technical and non-technical stakeholders, including senior leadership
- Design, maintain, and promote dashboards and automated reporting tools to empower stakeholders with self-serve, data-driven decision-making capabilities
- Build and optimize ETL data pipelines to automate reporting, support deep dive analysis and feature engineering for analytical models
Qualifications
- 5+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems
- Masters degree in a quantitative field such as mathematics, statistics, computer science or engineering
- Hands-on experiences with building marketing measurement solutions to quantify the business impact of marketing tactics and investments
- Strong background in statistics and quantitative analysis, with experience in applying advanced statistical techniques to real-world problems
- Expertise in at least one scripting language (ideally Python/R)
- Proficiency in SQL/Hive. Ability to write efficient SQL queries
- Strong business and product sense. Strong skills in shaping vague questions into well-defined analyses and success metrics that drive business decisions
- Excellent communication skills, able to lead initiatives and communicate findings to the leadership and cross-functional teams
- Experience leading key technical projects
- Strong Experimentation background
- Statistical rigor. Experience with causal inference projects
Locations
- San Francisco, CA, US; Remote, US (Remote)
Salary
114,297 - 235,319 USD / yearly
Estimated Salary Rangemedium confidence
140,000 - 200,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Python or R scriptingintermediate
- SQL and Hive proficiencyintermediate
- Statistics and quantitative analysisintermediate
- Advanced statistical techniquesintermediate
- Causal inferenceintermediate
- Experimentationintermediate
- Machine learning models (propensity, forecasting, LTV)intermediate
- Attribution methodologiesintermediate
- ETL data pipelinesintermediate
- Dashboard design and automated reportingintermediate
- Business and product senseintermediate
- Communication skillsintermediate
Required Qualifications
- 5+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems (experience)
- Masters degree in a quantitative field such as mathematics, statistics, computer science or engineering (experience)
- Hands-on experiences with building marketing measurement solutions to quantify the business impact of marketing tactics and investments (experience)
- Strong background in statistics and quantitative analysis, with experience in applying advanced statistical techniques to real-world problems (experience)
- Expertise in at least one scripting language (ideally Python/R) (experience)
- Proficiency in SQL/Hive. Ability to write efficient SQL queries (experience)
- Strong business and product sense. Strong skills in shaping vague questions into well-defined analyses and success metrics that drive business decisions (experience)
- Excellent communication skills, able to lead initiatives and communicate findings to the leadership and cross-functional teams (experience)
- Experience leading key technical projects (experience)
- Strong Experimentation background (experience)
- Statistical rigor. Experience with causal inference projects (experience)
Responsibilities
- Lead the design, implementation, and continuous improvement of advanced marketing measurement frameworks and statistical models to quantify marketing ROI across channels like paid media, organic social, email, events, webinars, and elearning
- Build and deploy statistical and machine learning models such as propensity, forecasting, and lifetime value (LTV) models to optimize marketing strategies and enhance audience targeting
- Develop and refine attribution methodologies to evaluate the effectiveness of marketing initiatives across multiple channels
- Assess the incremental impact of marketing activities using causal inference techniques and testing/experiment frameworks
- Conduct deep, strategic analyses to address key business questions, such as improving marketing ROI, optimizing marketing budget allocation, measuring marketing impact in mature and new markets, and identifying opportunities to increase advertiser growth and revenue
- Translate complex analytical findings into clear, actionable insights and strategic recommendations for both technical and non-technical stakeholders, including senior leadership
- Design, maintain, and promote dashboards and automated reporting tools to empower stakeholders with self-serve, data-driven decision-making capabilities
- Build and optimize ETL data pipelines to automate reporting, support deep dive analysis and feature engineering for analytical models
Tags & Categories
Data Scientist II, Growth Marketing
Data Scientist II, Growth Marketing
Job Description
Responsibilities
- Lead the design, implementation, and continuous improvement of advanced marketing measurement frameworks and statistical models to quantify marketing ROI across channels like paid media, organic social, email, events, webinars, and elearning
- Build and deploy statistical and machine learning models such as propensity, forecasting, and lifetime value (LTV) models to optimize marketing strategies and enhance audience targeting
- Develop and refine attribution methodologies to evaluate the effectiveness of marketing initiatives across multiple channels
- Assess the incremental impact of marketing activities using causal inference techniques and testing/experiment frameworks
- Conduct deep, strategic analyses to address key business questions, such as improving marketing ROI, optimizing marketing budget allocation, measuring marketing impact in mature and new markets, and identifying opportunities to increase advertiser growth and revenue
- Translate complex analytical findings into clear, actionable insights and strategic recommendations for both technical and non-technical stakeholders, including senior leadership
- Design, maintain, and promote dashboards and automated reporting tools to empower stakeholders with self-serve, data-driven decision-making capabilities
- Build and optimize ETL data pipelines to automate reporting, support deep dive analysis and feature engineering for analytical models
Qualifications
- 5+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems
- Masters degree in a quantitative field such as mathematics, statistics, computer science or engineering
- Hands-on experiences with building marketing measurement solutions to quantify the business impact of marketing tactics and investments
- Strong background in statistics and quantitative analysis, with experience in applying advanced statistical techniques to real-world problems
- Expertise in at least one scripting language (ideally Python/R)
- Proficiency in SQL/Hive. Ability to write efficient SQL queries
- Strong business and product sense. Strong skills in shaping vague questions into well-defined analyses and success metrics that drive business decisions
- Excellent communication skills, able to lead initiatives and communicate findings to the leadership and cross-functional teams
- Experience leading key technical projects
- Strong Experimentation background
- Statistical rigor. Experience with causal inference projects
Locations
- San Francisco, CA, US; Remote, US (Remote)
Salary
114,297 - 235,319 USD / yearly
Estimated Salary Rangemedium confidence
140,000 - 200,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Python or R scriptingintermediate
- SQL and Hive proficiencyintermediate
- Statistics and quantitative analysisintermediate
- Advanced statistical techniquesintermediate
- Causal inferenceintermediate
- Experimentationintermediate
- Machine learning models (propensity, forecasting, LTV)intermediate
- Attribution methodologiesintermediate
- ETL data pipelinesintermediate
- Dashboard design and automated reportingintermediate
- Business and product senseintermediate
- Communication skillsintermediate
Required Qualifications
- 5+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems (experience)
- Masters degree in a quantitative field such as mathematics, statistics, computer science or engineering (experience)
- Hands-on experiences with building marketing measurement solutions to quantify the business impact of marketing tactics and investments (experience)
- Strong background in statistics and quantitative analysis, with experience in applying advanced statistical techniques to real-world problems (experience)
- Expertise in at least one scripting language (ideally Python/R) (experience)
- Proficiency in SQL/Hive. Ability to write efficient SQL queries (experience)
- Strong business and product sense. Strong skills in shaping vague questions into well-defined analyses and success metrics that drive business decisions (experience)
- Excellent communication skills, able to lead initiatives and communicate findings to the leadership and cross-functional teams (experience)
- Experience leading key technical projects (experience)
- Strong Experimentation background (experience)
- Statistical rigor. Experience with causal inference projects (experience)
Responsibilities
- Lead the design, implementation, and continuous improvement of advanced marketing measurement frameworks and statistical models to quantify marketing ROI across channels like paid media, organic social, email, events, webinars, and elearning
- Build and deploy statistical and machine learning models such as propensity, forecasting, and lifetime value (LTV) models to optimize marketing strategies and enhance audience targeting
- Develop and refine attribution methodologies to evaluate the effectiveness of marketing initiatives across multiple channels
- Assess the incremental impact of marketing activities using causal inference techniques and testing/experiment frameworks
- Conduct deep, strategic analyses to address key business questions, such as improving marketing ROI, optimizing marketing budget allocation, measuring marketing impact in mature and new markets, and identifying opportunities to increase advertiser growth and revenue
- Translate complex analytical findings into clear, actionable insights and strategic recommendations for both technical and non-technical stakeholders, including senior leadership
- Design, maintain, and promote dashboards and automated reporting tools to empower stakeholders with self-serve, data-driven decision-making capabilities
- Build and optimize ETL data pipelines to automate reporting, support deep dive analysis and feature engineering for analytical models
Tags & Categories