Senior Data Scientist - Ad Measurement Science, Ad Measurement and Data Science

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Job summary

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 are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

Are you passionate about Deep Learning, Causal Inference, and Big Data Systems? Interested in building new state-of-the-art measurement products at petabyte scale? Be part of a team of industry leading experts that operates one of the largest big data and machine learning stacks at Amazon. Amazon is leveraging its highly unique data and applying the latest machine learning and big data technologies to change the way marketers optimize their advertising spend. Our campaign measurement and reporting systems apply these technologies on many billions of events in near real time.

You'll be one of the lead scientists tackling some of the hardest problems in advertising; measuring ads incrementality, providing estimated counterfactuals and predicting the success of advertising strategies. You and your team will develop state of the art causal learning, deep learning, and predictive techniques to help marketers understand and optimize their spend.

Some things you'll do in this role:

• Lead full life-cycle 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 is investing 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

Key job responsibilities

• Dive deep into petabyte-scale data to drive insights, identify machine-learning modeling gaps and business opportunities
• Establish scalable, efficient, automated processes for large-scale data analysis
• Run regular A/B experiments, gather data, and perform statistical analysis
• Work with applied scientists and product partners to develop new machine learning approaches, and monetization strategies
• Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication

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; 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 quantities (hundreds of millions/billions of rows) of data
• Combination of deep technical skills and business savvy enough 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.

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 https://www.amazon.jobs/en/disability/us.