Data Scientist - Specialist

EquifaxAlpharetta, GA
Hybrid

About The Position

Equifax Enterprise Innovation Office is seeking a Data Scientist who can integrate diverse big data assets into analytical solutions under management guidance to solve difficult business problems. With a strong heritage of innovation and leadership, we leverage our unique data, advanced analytics and proprietary technology to enrich the performance of businesses and the lives of consumers. Qualified candidates will have a passion for mathematics, statistics, AI/Machine learning, data gathering, and experience in financial modeling. The ideal candidate will combine the skills to create new prototypes with the creativity and thoroughness to ask and answer the deepest questions about the data, and to push the boundaries of what is possible with big data analytics/modeling. The ideal candidate will be passionate about exploring why and how models/techniques work and has a deep desire to explain the unexplainable. Equifax has a hybrid work schedule that allows for two days of remote work (Monday and Friday) with 3 days onsite (Tuesday thru Thursday) every week. This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support. This is a direct-hire role and is not open to C2C or vendors.

Requirements

  • Master’s degree or higher in Mathematics, Statistics, Data Science, Physics, Computer Science, Operations Research, Economics, Engineering or related quantitative field, PhD preferred
  • 7-10 years of experience in a related role, with experience demonstrating leadership capabilities
  • 5+ years experience applying predictive analytics and modeling to solve business problems
  • 5+ years of experience with Python, Tensorflow, SQL (strong skills and scripting experience), and Spark with advanced experience in data manipulation libraries (e.g., Pandas, Dask, Spark DataFrames)
  • Theoretical and practical understanding of algorithm time and space complexity, and a proven ability to apply this knowledge to develop efficient and scalable data science solutions
  • Excellent problem-solving skills, with the ability to navigate ambiguity and deliver results in a fast-paced environment

Nice To Haves

  • 1+ years Experience managing teams of at least two employees
  • Experience with large-scale data processing in distributed environments
  • Strong communication skills of analytical results to technical and non-technical audiences alike
  • Experience working on big data platforms (e.g., Google Cloud, AWS, Snowflake, Hadoop) a plus
  • Extensive experience with NLP (Natural Language Processing), LLMs (Large Language Models) and/or Generative AI
  • Agile development including Scrum
  • Ph.D. degree in mathematics, statistics, computer science, or related quantitative field

Responsibilities

  • Be an integral part of the Data Science Lab team that works closely with internal clients in all phases of prototype development and deployment
  • Research innovative data solutions (in distributed cloud computing constrained and unconstrained optimization) to solve real market problems
  • Develop analytical approaches to meet business requirements; this involves translating requests into use cases, test cases, preparation of training data sets and iterative product development
  • Work with key stakeholders and understand their needs to develop advanced solutions or improve existing solutions around big data and advanced analytics
  • Remain current on new developments in AI/Machine Learning, distributed algorithms, Big Data, Predictive Analytics, and Cloud Technology
  • Utilize subject matter expertise of data structures, analytics, algorithms/models, and strong computer science fundamentals to lead data preparation, analytics, and development of deployable solutions across multiple projects
  • Collect, analyze and interpret large data assets to define and build multiple innovative solution components leveraging business and technical expertise.
  • Lead the analytical strategy on critical technical capabilities
  • Perform as lead technical data scientist for multiple technical and business domains, collaborating with other teams to develop predictive models, risk assessments, fraud detection, recommendation engines, etc. encouraging enhanced solutions and asking questions
  • Evaluate the technical work of experienced data scientists guiding them on deliverable quality and accuracy

Benefits

  • comprehensive compensation and healthcare packages
  • 401k matching
  • paid time off
  • organizational growth potential through our online learning platform with guided career tracks
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service