Required Skills

Data Scientist

Work Authorization

  • US Citizen

  • Green Card

  • EAD (OPT/CPT/GC/H4)

  • H1B Work Permit

Preferred Employment

  • Corp-Corp

  • W2-Permanent

  • W2-Contract

  • Contract to Hire

Employment Type

  • Consulting/Contract

education qualification

  • UG :- - Not Required

  • PG :- - Not Required

Other Information

  • No of position :- ( 1 )

  • Post :- 24th Apr 2025

JOB DETAIL

  • Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline; OR 4 years of experience in statistics, mathematics, quantitative analytics, or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree.
  • 6 years of experience in a predictive analytics or data analysis OR Advanced Degree (e.g., Master's, PhD) in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline and 4 years of experience in predictive analytics or data analysis.
  • 4 years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models.
  • 4 years of experience in one or more dynamic scripted language (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models.
  • Proven experience writing code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency).
  • Strong experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc.
  • Strong experience in working with structured, semi-structured, and unstructured data files such as delimited numeric data files, JSON/XML files, and/or text documents, images, etc.
  • Demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.
  • Ability to assess and articulate regulatory implications and expectations of distinct modeling efforts.
  • Advanced experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic regression, discriminant analysis, support vector machines, decision trees, forest models, etc.
  • Advanced experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc.

Company Information