Director, Data Science - Marketing Decision Science

Key Skills

Java Programming, Analytical and Problem solving, Leadership, Python Programming, Framework, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, Looker, PyTorch, Tableau, TensorFlow, Apache Hive, Scikit-learn, R Programming, SPARK Programming, Mathematics

Job Description

The Marketing Decision Science team helps guide business strategy and drive marketing performance by synthesizing data and performance metrics into actionable insights for Walmart’s marketing teams, agency partners, and the broader Walmart enterprise. The team sits within the Customer Insights & Strategy organization and is part of the Walmart US Omni (eCommerce and Stores) business. This organization is helping accelerate Walmart’s aggressive growth both for online eCommerce and offline brick & mortar stores.

ROLE:

As the Director, Marketing Decision Science, you will lead the development of world-class analytics within the Walmart US Marketing team. You and your team are responsible for providing insights about marketing performance and optimization opportunities for our marketers, advertising agencies, internal partner teams, and senior leaders. You will help develop a holistic understanding of how marketing channels and other business levers work together to grow customer engagement, drive incremental sales, and contribute to longer term strategic objectives. You will be a true thought leader and partner in the Marketing organization that can work across key parts of Marketing (Performance Marketing, Brand Marketing, Data Engineering, Category Marketing), Merchandising and Finance to bring data-driven decision making to our marketing strategy. Given the size and scale of the Marketing at Walmart investment this position will be highly visible and have an opportunity to make a significant impact across the entire organization.

RESPONSIBILITIES:

• Lead the Marketing Decision Science team. Recruit and develop talent and build a world class marketing analysis group which that adds measurable value to our business partners and the Company.
• Lead the development and adoption of advanced media attribution models to measure and help optimize Walmart’s marketing investment across a wide range of short and long term business objectives.
• Develop, socialize & scale methodologies to solve key marketing measurement challenges. Apply marketing measurement techniques, including media mix models, multi-touch attribution, a/b testing, and causal inference models, to quantify the impact of marketing tactics on short and long term business and financial outcomes.
• Build & maintains strong working relationships across departments or teams based on trust and mutual respect. Communicate with senior stakeholders to balance stakeholder and analytics perspectives.
• Provide thought leadership in identifying opportunities to leverage advanced analytics drive incremental marketing performance and business value.
• Help inform the development of enterprise customer segmentation. Integrate marketing performance insights into our broader understanding of the factors affecting customer engagement and value.
• Support Walmart’s Category Marketing team by delivering empirically based insights into marketing’s contribution to product category goals regarding customer engagement, sales performance, and profitability.
• Support Walmart’s W+ customer loyalty program by optimizing the performance of marketing investments to drive program membership, retention, and profit.
• Partner with the Data Enablement and Tech teams to define requirements for analytics data pipelines, data management tools, and data visualization/reporting products.
• Partner with internal Marketing, Finance, Tech and Planning teams to develop forecasts for marketing’s incremental contribution to sales and digital traffic. Develop tools and lead training that enable Marketers partners to adopt an analytical mindset for their daily business decisions.
• Communicate technical material clearly to a range of audiences and build narratives that provides insight into the factors impacting business performance.

MINIMUM QUALIFICATIONS:

Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 6 years' experience in an analytics related field.

Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field.

Option 3: 8 years' experience in an analytics or related field.

PREFERRED QUALIFICATIONS:

• PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, or related field.
• 9 years' experience in data science, machine learning, optimization models, or related field.
• Successful completion of one or more assessments in Python, Spark, Scala, or R.
• 7 years’ experience using open-source frameworks (for example, scikit learn, tensorflow, torch).
• 4 years' supervisory experience.
• 5+ years of hands-on experience developing advanced marketing measurement methods, including marketing mix modeling solutions; proficiency with predictive modeling techniques and experience in leading media mix and predictive modeling initiatives.
• Working knowledge of supervised (GLM, Classification models, Ensemble techniques, Regularization techniques, Bayesian Models, Hierarchical models etc.) and unsupervised models (Clustering, Principal Component Analysis, etc.).
• Experience leveraging big data technologies (Hive/Hadoop) and modern data visualization tools (Tableau, ThoughtSpot, Looker) to blend data from multiple sources to help answer multi-dimensional business questions.
• Experience with various types of marketing data, including data regarding media (e. g., IRI, Kantar, Nielsen) and digital audience (e. g., DMPs), ad-serving (e.g., Google DCM, Atlas), and digital clickstream (e.g., Google Analytics, Adobe).
• Proven track record of thought leadership, innovation, and collaborative partnership with senior leaders in marketing and other business functions.
• Experience with causal inference measurement methodologies (a/b and multivariate testing, customer level synthetic control groups, Google Causal Inference, geo-based a/b testing).
• Working knowledge of Digital Marketing Channels (at least CPC Paid Search and Programmatic Display). Preference will be given to candidates with experience optimizing paid media channels through advanced Marketing and Ad Technology (i.e. Marin, Kenshoo, Google DoubleClick & Adwords, etc.).
• Strong organizational skills with a demonstrated ability to manage multiple priorities and lead complex projects with a high degree of ambiguity.
• Strong problem solving, analytical and quantitative skills and ability to synthesize findings into tangible actions that help drive business outcomes.
• A self-starter with a sense of ownership and accountability
• You have a passion for working in a fast-paced agile environment.

Minimum Qualifications...

Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.

Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 6 years' experience in an analytics related field.

Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field.

Option 3: 8 years' experience in an analytics or related field

Preferred Qualifications...

Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.

Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch)