[FULL TIME Remote] Data Scientist I

We're looking for a high-impact individual to join our team as a Data Scientist I! This is an exciting Remote opportunity with an immediate start. This position requires a strong and diverse skillset in relevant areas to drive success.

Earn a reliable and steady income of a competitive salary.   Under full supervision, helps advance Dataworks broad capabilities to use and deploy cutting edge data science and machine learning tools and methods in Dataworks projects, platforms and products.

Anchors current best practices by supporting the design and build of reusable data science assets.

Simultaneously works to help keep Dataworks on the bleeding edge by researching and understanding the very latest and most sophisticated methods and tools for grappling with large scale and complex problems.

Learns and helps apply descriptive, diagnostic, predictive, prescriptive and ensemble modeling, statistical techniques, and use of database tools and/or other approaches in quantitative analysis of complex business situations.

Helps provide recommendations to issues through knowledge of data scientific methods and machine learning / data engineering practices. Works in tandem with data scientists in peer positions.

Job Description / Responsibilities  The Data Scientist I plays a pivotal role, focused on supporting data science innovation within Dataworks, helping to define and build the Dataworks organization, and supporting more senior data scientists in the delivery of key business initiatives.

S/he acts as a  universal translator between IT, business, software engineers and data engineers, collaborating with these multi-disciplinary teams.

The Data Scientist I will contribute to the adherence of technical standards for data science and machine learning, including the design and construction of reusable data assets.

S/he will learn to work with large data sets and solve difficult analytical problems, often applying advanced methods.

S/he will support the creation and implementation of solutions from concept to production, using current and emerging technologies to evaluate trends and develop actionable insights and recommendations.

Day-to-day, s/he will be involved in code development and the support of small-scale deployments.  Understanding at a high-level both the business and technical problems Dataworks aims to solve  Exploring data and crafting models to answer core business problems that may not have a common blueprint  Supporting the invention of new approaches and algorithms for tackling data intensive problems  Helping the team scale up from  laptop-scale to  cluster scale problems by contributing to efforts to standardize and industrialize solutions  Delivering tangible value rapidly, collaborating with diverse teams of varying backgrounds and disciplines  Interacting with peer technologists from the broader enterprise and outside of FedEx (partner ecosystems and customers) to create synergies and identify opportunities for improvement  Following best practices for future reuse in the form of accessible, reusable patterns, templates, and code bases Skills/Abilities  Technical background in computer science, data science, machine learning, artificial intelligence, statistics or other quantitative and computational science  Experience or familiarity with designing and deploying large scale technical solutions, which deliver tangible, ongoing value  Direct experience or familiarity with building and deploying production systems that implement modern, data scientific methods at scale  Ability to context-switch, to provide support to dispersed teams which may need an  expert hacker to unblock an especially challenging technical obstacle, and to work through problems as they are still being defined  Demonstrated ability to support technical projects within a team, often working under tight time constraints to deliver value  An  engineering mindset, willing to make rapid, pragmatic decisions to improve performance, accelerate progress or magnify impact  Comfort with working with distributed teams on code-based deliverables, using version control systems and code reviews  Solid theoretical grounding in the mathematical core of the major ideas in data science  Good understanding or familiarity with a class of modelling or analytical techniques, often supported by Masters-level research in the subject  Familiarity with the mathematical  primitives and generalizations of data science  e.g., expertise in Linear Algebra, and Vector Calculus  Use of agile and devops practices for project and software management including continuous integration and continuous delivery  General knowledge or familiarity with some of the following common languages and tools:  SKLearn, XGBoost, Tensorflow, Pytorch, MLlib and other core machine learning frameworks  Python, Scala, Java and other modern programming lang