Senior Data Scientist I

RELX•Alpharetta, GA

About The Position

Develops, analyzes and models operational, economic, management, accounting and other organizational data to quantify the competitive performance of business segments, evaluate potential operational changes, and design new approaches and methodologies. Analyzes organizational data to recommend solutions to new and complex problems, develops innovative strategies, quantifies the competitive performance of the organization's operations and/or markets; models and evaluates the potential impact of changes. Applies and integrates statistical, mathematical, predictive modeling and business analysis skills to manage and manipulate complex high-volume data from a variety of sources.

Requirements

Minimum undergraduate degree in relevant field and 4+ years of relevant work experience
Or a master’s degree in a relevant field and 2+ years of relevant work experience.
Or a PhD in a relevant field.
Able to build or test new processes with senior guidance.
Domain expert in Data Science and/or Statistical Analysis to build advanced models and roll into production.
Able to scope out and execute new statistical steps with support/approval from senior contacts.
Independently creates typical data steps to prepare and process data for analysis.
Understands and utilizes novel data steps to prepare and process data for analysis.
Works across coding languages used in Data Science (e.g. Python, SQL, R, Java, and C++)
Chooses the right coding language to implement the solution to answer the business questions.
Develops project milestones and steps and independently executes for small-scale projects.
Independently executes project steps for more complex projects.
Expertise in the basic methods common to the discipline, industry, and domain.
Develops a basic understanding of adjacent approaches common to the discipline, industry, and domain.
Establishes stretch goals.
Willing to take risks and support team members and peers who do the same.
Keeps innovative efforts focused on the strategic needs of the team.
Takes initiative.
Proactively takes on issues negatively impacting the team.
Treats others with respect
Takes initiative to lead the team to address challenges within the scope of the team's responsibilities.
Fosters a team environment that emphasizes going above and beyond in action and accountability.
Can be counted on to uphold team commitments.

Responsibilities

Researching and developing statistical/machine learning models to analyze structured and unstructured data by ideating and experimenting with new methodologies to generate predictive scores and attributes.
Leading the design and development of data acquisition and machine learning models to produce key attributes that can leverage in risk segmentation models.
Ideating, researching, and designing new and innovative analytics and data science methodologies on large scale and complex data assets.
Storing, archiving, indexing, transferring, and analyzing large and complex datasets (structured and unstructured data).
Working with peers to share subject matter expertise, transfer skills, and develop knowledge base.
Exploring and mining new data sources to help optimize and validate existing models.
Having a thorough understanding of the team's core functions and technologies.
Staying current on emerging knowledge and technologies that impact the team's success and performance.
Being consulted by internal stakeholders to assess and troubleshoot challenges requiring their functional expertise.
Making important contributions to the team's success using their technical and professional expertise.
Applying organization and/or business knowledge to address issues facing the team.
Helping develop and articulate a sound business and technical strategy for the team.
Successfully applying expertise to advance the team's objectives.
Welcoming new ideas and methods to establish and achieve stretch goals within the team.
Establishing high standards that elevate the team's performance and benefit everyone on the team.
Consistently communicating team goals and milestone achievements to internal stakeholders.
Accepting new approaches and ideas from the team.
Encouraging internal stakeholders to share best practices and new ideas with the team.
Taking measures to advance new ideas within the team rather than discourage them.
All other duties as assigned.