Data Scientist

Top Required Skill Sets -

• 3+ years of professional experience as a data engineer
• 3+ years working with Python and SQL.
• Experience with state-of-the-art machine learning algorithms such as deep neural networks, support vector machines, boosting algorithms, random forest etc. preferred
• Experience conducting advanced feature engineering and data dimension reduction in Big Data environment is preferred
• Strong SQL skills in Big Data environment (Hive/ Impala etc.) a plus

Things that would stand out on resume -

• 1- Masters Degree in Computer Science & Data Science
• 2- Previous Company - Any Bank, Ecommerce

JOB DESCRIPTION:

• Equifax is looking for a Sr. Statistical Consultant/Sr. Data Scientist to join our world-class Global Identity and Fraud Analytics team. In this exciting role, you will have the opportunity to work on a variety of challenging projects across multiple industries including Financial Services, Telecommunications,
• eCommerce, Healthcare, Insurance and Government.
• In this position you will:
  • Work with various stakeholders such as Business Consultants, Senior Statisticians, Product Management, and Clients on the formulation and application of new modeling solutions for a variety of industry problems
  • Manipulate large data sets, integrate diverse data sources, data types and data structures into solutions
  • Develop analytical approaches to meet business requirements; this involves translating requests into use cases, test cases, preparation of training data sets and iterative algorithm development
  • Research new and advanced predictive modeling techniques as appropriate for a specific solution
  • Present results and recommendations to internal and external customers
  • Work with cross-functional teams to develop ideas and execute business plans
  • Develop solution prototypes and help integrate them with the product
  • Work closely with software development teams to communicate requirements and ensure quality of end-to-end deliverables of developed analytical solutions
  • Contribute to the team knowledge by keeping up with the state-of-the-art in machine learning applied to our domain

Desired Skills and Experience:

• Minimum 3 years of professional related work experience
• 1-3 years quantitative analytical experience, including conducting hands-on analytics projects using generalized regression models, Bayesian methods, random forest, gradient boosting, neural networks, support vector machine, clustering, and similar methodologies
• Proficiency skill in hands-on data mining and modeling projects with Python, R, and SQL
• Master's degree or higher in Mathematics, Computer Science , Engineering, Operations Research, Statistics or other related discipline
• Strong consultative acumen and ability to understand complex analytical solutions
• Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
• Ability to create new ideas for analytical solutions to address customer's business issues

Preferred Skills and Experience:

• 4+ years of professional experience as a data scientist or statistical modeler in at least one of the following: identity and fraud, credit risk, telecommunications, financial services, payment, ecommerce, B2B or B2C, marketing, insurance, or security analytics arena.
• 4+ years working with Python and SQL.
• Experience with state of the art machine learning algorithms such as deep neural networks,support vector machines, boosting algorithms, random forest etc. preferred
• Experience conducting advanced feature engineering and data dimension reduction in Big Data environment is preferred
• professional experience as a data scientist or statistical modeler in identity and fraud, credit risk, telecommunications, financial services, payment, ecommerce, B2B or B2C, marketing, insurance, or security analytics arena is a plus
• Strong SQL skills in Big Data environment (Hive/ Impala etc.) a plus
• Proficient with any programming languages such as Python , Java, Scala a plus
• Experience working with very large datasets, knowledge of distributed computing tools (Hadoop Streaming, MapReduce, Spark) a plus
• Exposure to Visualization tools such as Tableau a plus
• Extensive knowledge in fraud prevention methods and detection tools a plus
• Strong knowledge of credit bureau data and business problems in financial services and/or telecommunications a plus.