Data Scientist, Database Migration Accelerator

Key Skills

Java Programming, Python Programming, SQL, Apache Hadoop, Scala Programming, MATLAB Programming,

Job Description

Job summary

Come and join the Database Migration Accelerator team that helps our customers migrate to the cloud. We are on a mission to transform legacy enterprise workloads into modern AWS native application architectures. We achieve this by utilizing cutting edge tools, sophisticated engineering systems and database expertise. We provide fixed price and high speed migrations to the cloud. Database Migration Accelerator is combining various AWS cloud platform services into one product which would serve our customers.

We have an opportunity for an Data Scientist who is passionate about mathematical optimization with developing new offerings for the cloud and is enthusiastic about applying bold new ideas to real-world problems.

• Joining the AWS Database Services team as an Data Scientist gives you the opportunity to:
• Work for a company that’s at the forefront of the cloud computing space
• Be a part of something unique what no other previously developed and was successful.
• Design mathematical optimization algorithms to intelligently move enterprises to the cloud.
• Truly own solution from concept design through development to production
• Join the team whose activities are regularly called out publicly by AWS CEO Andy Jassy
• We welcome teammates who are enthusiastic, empathetic, curious, motivated, reliable, and able to collaborate with a diverse team of peers.

Key job responsibilities

• Implement statistical methods to solve specific business problems utilizing code (Python, R, Scala, etc.)
• Directly contribute to the design and development of capacity planning models and other predictive models with limited guidance
• Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters
• Collaborate with product management, research science, data engineering, and business leaders to define product requirements, provide analytical support, and communicate feedback; develop, test and deploy a wide range of statistical, econometric, and machine learning models
• Build customer-facing reporting tools to provide insights and metrics which track model performance and explain variance
• Written and verbal communication to business customers with various levels of technical knowledge, educating them about our solutions, as well as sharing insights and recommendations
• Earn the trust of your customers by continuing to constantly obsess over their needs and helping them solve their problems by leveraging technology
• Manage critical initiatives to enforce standard work and reduce waste

A day in the life

Work/Life Balance

Our team places value on work-life balance. Our team is global, based in the US and Poland. Our Poland teams typically start later in the day to have a couple of hours of overlap with US teams.

Mentorship & Career Growth

Our team is dedicated to supporting new team members in an environment that celebrates knowledge sharing and mentorship. Our senior engineers mentor more junior engineers through one-on-one mentoring and collaborative code reviews. Projects and tasks are assigned in a way that leverages your strengths and helps you further develop your skillset.

Inclusive Team Culture

We get to build a really cool service and the main contributing factor to our success is the inclusive and welcoming culture that we embody every day.

About the team

We are a team of professionals that are forward-looking and using latest technology offerings (AWS cloud services, Machine Learning, Mathematical Optimization, Relational and NoSQL databases) to build new capability to operationalize and automate migration methodologies. Databases Services at AWS cover a range of data platforms including Amazon Aurora, DynamoDB, Redshift, Athena, as well as AWS Database Migration Service, Data Pipeline, Glue and more. As each service grows, so does adoption by customers world-wide.

BASIC QUALIFICATIONS

• Master's degree in Statistics, Mathematics, Data Science, Business Analytics, Economics, Finance, Engineering, or Computer Science, or a related quantitative field or equivalent experience
• 2+ years of experience with data querying languages (e.g. SQL, Hadoop/Hive, Scala) and statistical/mathematical software (e.g. R, Matlab, Stata)
• Experience applying various machine learning techniques, and understanding the key parameters that affect their performance
• Ability to work on a diverse team or with a diverse range of coworkers

PREFERRED QUALIFICATIONS

• Advanced knowledge and expertise with data modelling skills, advanced SQL for acquiring and transforming data
• Depth and breadth in quantitative knowledge
• Proven ability in quantitative modeling, statistical analysis skills and problem-solving skills.
• Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment
• Experience with causal inference, applied time series modeling or machine learning forecasting applications is a plus
• Proven verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams and business audiences