Data Scientist I

Description

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 languages
• MLFlow, Databricks, Spark, Kafka and other data tools and frameworks
• CPLEX, Gurobi and other similar optimization modeling packages

Domicile Information: 

This position can be domiciled anywhere in the United States. The ability to work remotely within the United States may be available based on business need. 

Minimum Education

Bachelors Degree with at least One year experience or Master’s Degree or equivalent in computer science, operations research, statistics, applied mathematics or related quantitative discipline.

Minimum Experience

Strong knowledge in advanced data science and machine learning tools and methods, including the iterative development of analysis pipelines to provide insights at scale. Strong knowledge and experience in conducting end-to end analyses, including data gathering and requirements specification, processing, analysis, and presentations. Strong understanding of the transportation industry, competitors, and evolving technologies. Experience as a member of multi-functional project teams. Strong oral and written communication skills.

Knolwedge, Skills and 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 languages MLFlow, Databricks, Spark, Kafka and other data tools and frameworks CPLEX, Gurobi and other similar optimization modeling packages

Preferred Qualifications:  

Pay Transparency: This compensation range is provided as a reasonable estimate of the current starting salary range for this role across all potential locations. If this opportunity includes multiple job levels, the range is a reasonable estimate of the current starting salary for the lowest level to the current starting salary of the highest level. Actual starting pay would be determined by experience relative to the job, market level, pay at the location for this job and other job-related factors permitted by law. An employee may be eligible for additional pay, premiums, or bonus potential. The Company offers eligible employees health, vision and dental insurance, retirement, and tuition reimbursement.

Pay: U.S. Pay Range: $5,627 - $8,440

Additional Details: Upload current copy of Resume (Microsoft Word or PDF format only) and answer job screening questionnaire by 12/23/2024.

FedEx Dataworks is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Dataworks does not discriminate against qualified individuals with disabilities in regard to job application procedures, hiring, and other terms and conditions of employment. Further, Dataworks is prepared to make reasonable accommodations for the known physical or mental limitations of an otherwise qualified applicant or employee to enable the applicant or employee to be considered for the desired position, to perform the essential functions of the position in question, or to enjoy equal benefits and privileges of employment as are enjoyed by other similarly situated employees without disabilities, unless the accommodation will impose an undue hardship. If a reasonable accommodation is needed, please contact DataworksTalentAcquisition@corp.ds.fedex.com.