Senior Data Scientist

Key Skills

Java Programming, Analytical and Problem solving, Python Programming, SQL, AWS, Machine learning techniques, Data science techniques, Data Mining, MATLAB Programming, Data Modeling, R Programming, Amazon RedShift, Amazon EMR, SPARK Programming, SAS, Large scale data processing

Job Description

Amazon's Sponsored Products advertising business is one of the fastest growing areas in the company. Have you ever wondered what happens behind that “Sponsored” label you see in search results on Amazon? Hint: it involves a lot of interesting tech delivered by a great team.

The Sponsored Products Marketplace team optimizes the systems and ad placements to match demand with supply using a combination of data-driven product innovation, machine learning, big data analytics, and low latency/high-volume engineering. By the time organic search results are ready, we've processed all of the potential ads and determined which ones are going to be shown. We do that billions of times per day, resulting in millions of engagements with products that might otherwise not have been seen by shoppers.

The business and technical challenges are significant. Fortunately, we have a broad mandate to experiment and innovate, and a seemingly endless range of new opportunities to build a big, sustainable business that helps Amazon continuously innovate on behalf of all customers.

We're looking for customer-obsessed, innovative, professional data scientist who can help us take our products to the next level of functionality, quality and performance. We embrace leaders with a startup mentality — those who seek a disruptive yet clear mission and purpose, have an unambiguous owner's mindset, and are relentlessly obsessed with delivering amazing products. As a Sr. Data Scientist on our team, you will be responsible for building and managing modeling projects, identifying data requirements, and delivering methodology and tools that are statistically grounded around our advertiser facing products such as new targeting controls, ad sourcing techniques, automated optimization strategies, and advertiser-facing recommendations. You should have superb analytical, technical, business and communication skills to be able to work with business and technology leaders to define and prioritize key business questions, build data acquisition processes, data sets, statistical models and analyses that answer those questions. If this sounds like your sort of challenge, read on.

Characteristics indicative of success in this role:

• Highly analytical: You solve problems in ways that can be backed up with verifiable data. You focus on driving processes, tools, and statistical methods which support rational decision-making.
• Technically fearless: You aren't satisfied by performing 'as expected' and push the limits past conventional boundaries. Your dial goes to '11'.
• Engaged by ambiguity: You're able to explore new problem spaces with unique constraints and non-obvious solutions.
• Team obsessed individual contributor: You help grow your team members to achieve outstanding results. You've learned that big plans generally involve collaboration and great communications.
• Quality obsessed: You recognize that professional engineers ship complete, tested software to avoid getting trapped in a sea of technical debt. You balance speed with quality.
• Humbitious: You’re ambitious, yet humble. You recognize that there’s always opportunity for improvement. You use introspection and feedback from teammates and peers to raise the bar.

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 processing, filtering, and presenting large quantities (100K to Millions of rows) of data
• Experience with statistical analysis, data modeling, machine learning, optimizations, regression modeling and forecasting, time series analysis, data mining, and demand modeling
• Experience applying various machine learning techniques, and understanding the key parameters that affect their performance
• Excellent written and verbal communication skills. Strong ability to interact, communicate, present, and influence within multiple levels of the organization.
• Experience with Predictive analytics (e.g., forecasting, time-series, neural networks) and Prescriptive analytics (e.g., stochastic optimization, bandits, reinforcement learning)

PREFERRED QUALIFICATIONS

• Master's degree in Operations Research Engineering, Statistics or related field
• 10+ years professional experience in large-scale data science or advanced analytics
• Experience with AWS and data-oriented tools such as Redshift, Spark, EMR
• Experience in online advertising domain (particularly, ad targeting and serving)
• Experience as team leader