Senior Data Scientist, Brand Growth

Key Skills

Java Programming, Design, Python Programming, SQL, Apache Hadoop, A/B Testing, Deep Learning, MATLAB Programming, Natural Language Processing (NLP), Apache Hive, Apache Pig, Elasticsearch, R Programming, Amazon EMR, SPARK Programming, SAS, Descriptive analysis , Data Analysis

Job Description

Job summary

Location is virtual; anywhere in the US is fine. Rest of the team is in NYC and Seattle.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. 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!

We are seeking a entrepreneurial, innovative and self-driven Senior Data Scientist to join our team, and build a brand new Advertising product together from the ground up. Your mission will be to leverage science and technology to help hundreds of thousands of independent sellers grow their business on WW Amazon marketplaces building customer loyalty. You will generate actionable business insights to help connect brand owners with reviewers and potential shoppers on Amazon websites and video channels (IMDB, FireTV, Twitch, Amazon.com etc). You can change the life of local business owners while taking ownership to solve technical challenge from delivering millions of global advertising campaigns and generating brand insights through 100s of internal and external integrators with superfast response time. Brand Growth is part of Amazon Advertising’s Advertiser Control and Experimentation (ACE) org with opportunity to deliver social impact, own technical problems, thought diversity, and business impact.

As a Senior Data Scientist on this team you will:

• Lead Data Science solutions from beginning to end.
• Deliver with independence on challenging large-scale problems with complexity and ambiguity.
• Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data.
• Build Machine Learning and statistical models to solve specific business problems.
• Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.
• Analyze historical data to identify trends and support optimal decision making.
• Apply statistical and machine learning knowledge to specific business problems and data.
• Formalize assumptions about how our systems should work, create statistical definitions of outliers, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed.
• Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.
• Build decision-making models and propose effective solutions for the business problems you define.
• Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication.

Why you will love this opportunity: Amazon has invested heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.

Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.

Team video ~ https://youtu.be/zD_6Lzw8raE

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

Add to BQs:

• 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.
• Excellent verbal and written communication skills with the ability to advocate technical solutions for science, 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 computational advertising desired, but not required.