Equifax Enterprise Innovation Office is seeking a Data Scientist to integrate diverse big data assets into analytical solutions to solve business problems
Requirements
- Master’s degree in Mathematics, Statistics, Data Science, Physics, Computer Science, Operations Research, Economics, Engineering or related quantitative field, or a Bachelor's degree with equivalent relevant experience
- 2+ years of experience applying predictive analytics and modeling to solve business problems; this can include internships and/or a Master’s Degree
- 1-3 years of experience with Python, Tensorflow, SQL (solid skills and scripting experience), and Spark with experience in data manipulation libraries (e.g., Pandas, Dask, Spark DataFrames)
- Foundational understanding of algorithm time and space complexity, and an ability to apply this knowledge to develop efficient data science solutions
- Experience with large-scale data processing in distributed environments
- Strong problem-solving skills, with the ability to navigate ambiguity and deliver results in a fast-paced environment
- Familiarity or exposure to NLP (Natural Language Processing), LLMs (Large Language Models) and/or Generative AI
Responsibilities
- Contribute as part of the Data Science Lab team, collaborating with internal clients in various phases of prototype development and deployment
- Explore and apply innovative data solutions (in distributed cloud computing constrained and unconstrained optimization) to solve real market problems
- Leverage expertise in data structures, analytics, algorithms/models, and computer science fundamentals to prepare, analyze, and develop robust, deployable solutions
- Design, write, and optimize complex SQL queries for data extraction, transformation, and analysis, often dealing with large datasets
- Assist in the design, development, and implementation of NLP and LLM solutions, including text classification, summarization, and NER (Name Entity Recognition), leveraging state-of-the-art embedding models like Gemini and BERT
- Contribute to the development and implementation of solutions for efficient processing of large-scale data using distributed systems
- Data Quality & Labeling: Demonstrate a commitment to data integrity by patiently and meticulously performing essential tasks such as data labeling, classification verification, and anomaly detection
Other
- Master’s degree in Mathematics, Statistics, Data Science, Physics, Computer Science, Operations Research, Economics, Engineering or related quantitative field, or a Bachelor's degree with equivalent relevant experience
- 2+ years of experience applying predictive analytics and modeling to solve business problems; this can include internships and/or a Master’s Degree
- Strong communication skills of analytical results to technical and non-technical audiences alike
- 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
