Principal, Data Scientist, Search & Social Marketing

Key Skills

Java Programming, Python Programming, SQL, Apache Hadoop, Machine learning techniques, Data Modeling, Apache Hive, Apache Pig, Elasticsearch, R Programming, SPARK Programming, SAS, Large scale data processing

Job Description

Amazon’s Search & Social Marketing team manages one of the world’s largest demand-side advertising programs on search engines and withing social media apps, engaging with customers (and importantly, future customers) when they are not already shopping on Amazon. Whether that is by putting engaging lifestyle imagery in a user’s Instagram feed, presenting an engaging influencer-generated unboxing video on TikTok, or providing the right search result on Google, this organization owns the systems and vision to make that happen. On any given day our products are managing more than 500 million live ads worldwide, supporting customers in more than 25 countries, and driving a significant share of traffic to Amazon’s stores. With the level of marketing spend we manage and impact that we drive, it is essential that we are interatively driving improvements in our methods and systems to ensure we are getting the highest possible return on our investments.

We are seeking a Principal Data Scientist to lead organization wide initiatives to further optimize our marketing programs through the practical application of novel scientific and technical solutions. It's an exciting and evolving area and that will require working across a number of Amazon teams, including our parent organization -- Traffic & Marketing Technology, other science teams, Amazon's Operations org, Finance, worldwide stakeholder teams, and more. As a leader in Search & Social Marketing the decisions you drive and strategies you help to create will affect the architecture and science used by systems that solve some of our most complex business problems.

Key job responsibilities

As a Principal Data Scientist in Search & Social Marketing you will work across a number of organizations to identify opportunities for us to better integrate systems, utilize various models, build and improve experiementation systems, and evolve our system architecture. As one of the highest priority goals you will take on, you will collaborate with various teams to identify different signals/inputs that we should incorporate into our bidding, and ranking systems to ensure that we are maximizing our return on investment by capturing the network effects that our marketing actions have across various systems within Amazon.

BASIC QUALIFICATIONS

• MSc in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
• 10+ years of practical experience applying DS to solve complex problems;
• Experience with statistics packages such as R, SAS or Python;
• SQL experience
• Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives. Defining and identifying success
• Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts.
• Experience with end to end feature development (owning feature definition, roadmap development and experimentation

PREFERRED QUALIFICATIONS

• Experience with problem framing across multiple sub-domains, including forecasting, anomaly detection, classification, and regression.
• Expert level knowledge in statistics.
• Understanding of various data applications used across large scale distributed systems ( EMR, Spark, Elasticsearch, Hadoop, Pig, and Hive).
• Experience leveraging existing ML methods and techniques at scale in production oriented environments.
• Combination of technical and business acumen, with ability to advocate technical solutions for science with engineering and business audiences.
• Ability to develop experimental and analytical plans for data modeling, use effective baselines, and accurately determine cause-and-effect relations.
• Experience in demand-side marketing systems