Senior Data Scientist, Amazon Ads

Key Skills

A/B Testing, Amazon EMR, Analytical and Problem solving, Apache Hadoop, Apache Hive, Apache Pig, Design, Elasticsearch, Java Programming, Large scale data processing, MATLAB Programming, MS Dynamics, Python Programming, R Programming, SAS, SPARK Programming, SQL

Job Description

Amazon Ads, one of the fastest growing businesses within Amazon, is building a large-scale marketing tech-solution from ground-up. This solution will serve thousands of internal and external customers worldwide and will solve some of the most complex problems that are yet to be solved in the industry.

As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

To achieve this ambitious goal, we seek a Senior Data Scientist who will be obsessed with delivering the most customer-centric experience for our customers.

We are looking for a highly motivated, analytical and detail-oriented candidate to help build scalable solutions that supports our Content Management System organization. You will build a new suite of tools to automate content management around content measurement, discoverability, distribution, and work management. You will be part of highly motivated team of product managers and developers who will solve some of the most complex problems using the most advance technologies.

To be successful in this role, you will be a pragmatic generalist. You can contribute to each layer of a data solution and work closely with engineers and product managers to prototype predictive analytic models and review key results with business leaders and stakeholders. Your work exhibits a balance between scientific validity and business practicality. You will turn ambiguous business questions into clearly defined problems, develop quantifiable metrics and robust machine learning models from imperfect data sources, and deliver results that meet high standards.

Key job responsibilities

• Build long term vision, roadmap and execution plan
• Interview stakeholders to gather business requirements and translate them into concrete requirement for data science projects
• Define metrics and design algorithms to estimate accuracy of the tools.
• Define and conduct experiments to optimize the outcome, and communicate insights and recommendations to product, engineering, and business teams
• Work with data engineers and software development engineers to deploy models and experiments to production
• Identify and recommend opportunities to automate systems, tools, and processes
• Provide support on hiring Science team and mentor them.

BASIC QUALIFICATIONS

• Bachelor's Degree
• 5+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
• 4+ years working as a Data Scientist
• Experience in as many of the following areas: causal inferencing ,multi-variate testing & design, A/B testing & design, descriptive analytics, and regression analysis.
• Good understanding of supervised and unsupervised learning models.

PREFERRED QUALIFICATIONS

• Advanced degree in Computer Science, Mathematics, Statistics, Economics, or related quantitative field.
• Broad knowledge of ML methods, statistical analysis, and problem-solving skills.
• Expert level knowledge in statistics and sophisticated user of statistical tools.
• Experience in data applications using large scale distributed systems (e.g. EMR, Spark, Elasticsearch, Hadoop, Pig, and Hive).
• Experience processing, filtering, and presenting large data sets (hundreds of millions/billions of rows).
• Combination of deep technical skills and business sense, to interface with all levels and disciplines within our customer’s organization.
• Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.