Data Scientist, Driver 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

Do you enjoy transforming data into actionable insights and taking data-driven approach to solving complex business problems? The Last Mile DSP and Driver Sciences team is looking for a talented Data Scientist to drive world-class analysis and guide strategic business decisions to Improve DA Retention.

At Amazon, we are working to be the most customer-centric company on earth -- including how we fulfill and deliver customer orders. The goal of Amazon’s Service Partner (DSP) Management Team is to exceed the expectations of our customers by ensuring that their orders, no matter how large or small, are delivered as quickly, accurately, and cost effectively as possible. To meet this goal, Amazon is continually striving to innovate and provide best in class experience through the introduction of pioneering new products and services in the last mile space.

As a Data Scientist in the team, you will be driving the analytics roadmap and will provide descriptive and predictive solutions to the product management team through a combination of data mining techniques as well as use statistical and machine learning techniques for segmentation and prediction. You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards.

The ideal candidate is an experienced and motivated Data Scientist (DS) with outstanding leadership skills, proven ability to build and manage Large-scale modeling projects, identify data requirements, and build methodology and tools that are statistically grounded. The candidate will be an expert in the areas of data science, machine learning and statistics, and is comfortable facilitating ideation and working from concept through to execution. The successful Data Scientist will have the extreme bias for action needed in a startup environment.

To succeed in this role you should be passionate about working with large datasets and be someone who loves to bring data together to answer key business questions. You should have deep expertise in the creation and management of datasets and the proven ability to translate the data into meaningful insights. You should have a solid understanding of efficient and scalable data mining and an ability to use the data in financial and statistical modeling.

Key job responsibilities

• Demonstrate through technical knowledge on Statistical modeling, Probability and Decision theory, Operations Research techniques and other quantitative modeling techniques
• Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area
• Innovate by adapting new modeling techniques and procedures
• You should be passionate about working with huge data sets and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets
• You should have exposure at implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports. These solutions will be fault tolerant, self-healing and adaptive
• You will extract huge volumes of data from various sources and construct complex analyses.
• You should be detail-oriented and must have an aptitude for solving unstructured problems. You should work in a self-directed environment, own tasks and drive them to completion

You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions and to build data sets that answer those questions. You own customer relationship about data and execute tasks that are manifestations of such ownership, like ensuring high data availability, low latency, documenting data details and transformations and handling user notifications and training

You will work with distributed machine learning and statistical algorithms upon a large Hadoop cluster to harness enormous volumes at scale to serve our customers

BASIC QUALIFICATIONS

• Master’s degree (or Bachelors degree or 5+ years of experience) in a quantitative discipline such as Statistics, Mathematics, Data Science, Business Analytics, Economics, Finance, Engineering, or Computer Science
• 2+ years of experience working as a data scientist or a similar role involving data extraction, analysis, statistical modeling, and communication
• 2+ years of experience using data querying languages (e.g. SQL, Hadoop/Hive)
• Masters in quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent)
• 3+ years of experience working in data science in a consumer product company, managing Machine Learning Scientists, Data Scientists, Research Scientists, Applied Scientists, and/or Economists
• Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
• Ability to manage and quantify improvement in customer experience or value for the business resulting from research outcomes
• Experience using a scripting language for managing large datasets
• Ability to quickly adapt to changing priorities and generate innovative solutions in an extremely fast-paced environment
• Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to non-experts.

PREFERRED QUALIFICATIONS

• Master’s Degree in Computer Science, Systems Analysis, or related field
• Skilled with Python, Java, C++, or other programming language, as well as with R, SAS, MATLAB or similar scripting language
• Advanced knowledge and expertise with Data modelling skills, Advanced SQL with Oracle, MySQL, and Columnar Databases
• Functional knowledge of AWS platforms such as S3, Glue, Athena, Sagemaker.
• Experience leading cross-functional projects and effectively communicating with both business and technical teams
• 3+ years’ experience with BI/DW/ETL projects.
• Technically deep and business savvy enough to interface with all levels and disciplines within the organization.

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.