Sr. Marketing Data Scientist, AWS Marketplace Demand Generation

2 months ago

Boston, United States oilandgas.org.uk Full time

In this role, you will develop data-driven solutions to optimize our marketing efforts across messaging, channels, and features. You will collaborate with stakeholders in marketing, product, engineering, and sales to enhance customer engagement relevance, predict customer needs, and measure marketing impact. You will institute analytical rigor across marketing and co-sell initiatives and in doing so help scale and optimize our impact for buyers and partners.


Key job responsibilities
  1. Multi-Touch Attribution (MTA) & Market Mix Modeling (MMM): Develop and maintain sophisticated attribution models to accurately measure the impact of marketing channels and optimize cross-channel marketing strategies.
  2. Marketing Impact Measurement: Apply causal inference techniques such as double robust regression, propensity score matching, and other econometric models to quantify the true impact of marketing initiatives.
  3. Customer Lifetime Value (CLV) Prediction: Create predictive models to estimate CLV and inform strategies for customer acquisition, retention, and upsell opportunities.
  4. A/B Testing & Experimentation: Partner with marketing teams to design, execute, and analyze A/B tests and controlled experiments that optimize campaigns and marketing efforts.
  5. Customer Segmentation & Personalization: Design and implement data-driven segmentation strategies to identify customer personas and personalize marketing communications at scale.
  6. Conversion Optimization: Build models to prioritize high-quality leads for sales teams, improving sales efficiency and conversion rates.
  7. Transform Data into Insights: Analyze complex data sets and transform them into actionable insights that inform marketing strategy and drive business results.
  8. Analyze Buyers' Journeys: Build measurement and analysis strategies to understand buyers' journeys across a marketplace of solutions to provide recommendations on how to better meet customer needs and enhance our customer's experience.
  9. Campaign Optimization: Build predictive models to improve campaign targeting, segmentation, and budget allocation, maximizing efficiency and conversion rates.
  10. Inform, Educate and Enable: Be able to present and communicate findings to senior leaders as strategy insight. Deliver and maintain training and resource materials, highlighting best practices and opportunities for efficiency.

About the team

AWS Marketplace enables enterprises and startups to optimize how they discover, migrate, procure, and deploy trusted third-party software, data, and professional services as they migrate to and build in the cloud. The AWS Marketplace Marketing team exists to support this growth with global go-to-market (GTM) strategies and programs intended to accelerate discovery and adoption of AWS Marketplace-listed solutions.


BASIC QUALIFICATIONS
  1. Bachelors degree with emphasis in business/marketing or Data Science, Statistics, Computer Science, Mathematics
  2. 5+ years experience in a Marketing Analytics/Business Intelligence role, ideally in a B2B, SaaS and/or marketplace business environment
  3. Exposure to B2B marketing funnel, Marketing KPIs such as conversion rates, Cost per lead, cost of customer acquisition, and Marketing attribution and ROI.
  4. Proficiency in programming languages such as Python or R, with experience in data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn).

PREFERRED QUALIFICATIONS
  1. Master's in Data Science, Statistics, Computer Science, Mathematics, or a related field with minimum 2 years of relevant work experience
  2. Experience or certifications with Salesforce, Marketo, Eloqua, or HubSpot; Web Metrics certification (like Adobe or Google Analytics)
  3. Prior experience working with either ISV B2B Marketing, or Marketplace business models
  4. Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Keras) and familiarity with deep learning techniques.
  5. Strong understanding of statistical analysis and modeling techniques, including regression, clustering, and causal inference.
  6. Experience with building and maintaining data pipelines using tools such as Apache Spark, SQL, or ETL processes.
  7. Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) and data storage solutions (e.g., SQL and NoSQL databases)

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit here.

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