Senior Data Scientist

Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds,  and make a meaningful impact, we want to hear from you.

The Equifax Data Science Lab is seeking a Senior 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 2 days of remote work (Monday and Friday), with 3 days onsite (Tuesday, Wednesday, Thursday) every week.

This role reports to our office in Alpharetta, Georgia or midtown ATL (OAC).

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.

What you will do 

• Utilize combined knowledge of data structures, analytics, algorithms/models, and strong computer science fundamentals to independently prepare datasets, conduct analytics, and develop deployable solutions.

• Collect, analyze and interpret large data assets to define and build multiple innovative solution components leveraging business and technical expertise.  Support the analytical strategy by understanding critical technical capabilities and suggesting opportunities. 

• Lead the development of projects with multiple deliverables, leveraging business and technical expertise.  

• Work on high-complexity tasks in problems often within multiple business or analytical domains,  collaborating with other teams to develop predictive models, risk assessments, fraud detection, recommendation engines, etc. encouraging enhanced solutions. 

• Package, summarize, visualize and perform storytelling on analytical findings and results for management and business users.

• Communicate results to external stakeholders and mid level leadership, able to communicate business impact of work.

• Evaluate the technical work of peer and junior data scientists, guiding them on deliverable quality and accuracy.

• SQL Mastery & Optimization: Design, write, and optimize highly complex SQL queries for data extraction, transformation, and analysis, often dealing with massive datasets.

• Design, develop, and implement advanced NLP and LLM solutions, including text classification, summarization, and NER (Name Entity Recognition), powered by state-of-the-art embedding models like Gemini and BERT.

• Data Quality & Labeling: Demonstrate an unwavering commitment to data integrity by patiently and meticulously performing essential tasks such as data labeling, classification verification, and anomaly detection.  

What experience you will need 

• BS or MS degree in Computer Science or equivalent discipline.

• 5-7 years of experience as a Data Scientist or other analytical role.

• Extensive experience with Scala or Python, Tensorflow, SQL (strong skills and scripting experience), and Spark with advanced experience in data manipulation libraries (e.g., Pandas, Dask, Spark DataFrames).

• Demonstrated experience with NLP (Natural Language Processing), LLMs (Large Language Models) and/or Generative AI. 

• Proven track record of designing and developing predictive models in real-world applications.

• Experience with model performance evaluation and predictive model optimization for accuracy and efficiency.

• Experience with Distributed Data Processing - Architect, develop, and implement solutions for efficient processing of large-scale data.

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