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Sr. Data Scientist 2771

Role overview

Qualifications

  • Bachelor's degree and a minimum of 5 years related experience, or in lieu of a degree, a combined minimum of 9 years higher education and/or work experience, including a minimum of 5 years related experience
  • Proficiency with pertinent statistical software and languages and tools
  • Experience analyzing large data sets
  • Intermediate level knowledge of Structured Query Language (SQL) and Not Only Structured Query Language (nSQL)

Responsibilities

  • Work with large and complex data sets to solve unstructured problems using different analytical and statistical approaches for multiple products independently
  • Lead sourcing, ingesting, and cleaning of data sets in preparation for analysis, and assist more experienced data scientists to productionize and scale data cleanup process
  • Build complex econometric, statistical and machine learning models for various problems inclusive of classification, clustering, pattern analysis, sampling, and simulations
  • Create model outputs for business discussions to display model outcomes, impact and business value

Key facts

Hard skills

Other skills

  • Problem Solving
  • Team Leadership
  • Communication

About the company

CTI Staffing logo

CTI Staffing

Staffing & Recruiting

Unknown

Company details

IndustryStaffing & Recruiting
Company size11 - 50

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Job description

This is a remote position.

POSITION RESPONSIBILITIES:

Work with large and complex data sets to solve unstructured problems using different analytical and statistical approaches for multiple products independently.
Lead sourcing, ingesting, and cleaning of data sets in preparation for analysis, and assist more experienced data scientists to productionize and scale data cleanup process. Ensure data is stable, accounting for complex data drift in development and production.
Build complex econometric, statistical and machine learning models for various problems inclusive of classification, clustering, pattern analysis, sampling, and simulations.
Commit complex code into model repository and promote complex models into production system.
Develop champion/challenger models and adjust models accordingly.
Implement framework for building self-healing models.
Select and refine models, taking into account performance, reliability and stability metrics and business feedback.
Draft model refinement educational materials for data users.
Create model outputs for business discussions to display model outcomes, impact and business value. Lead less experienced team members in creating consumable model outputs. Attend stakeholder meetings to discuss concerns, opportunities and production challenges.
Work with more experienced data scientists to develop new research approaches and provide initial assessment of how techniques will be adapted based on client needs.
Review code to ensure it is efficient, accurate, and using best practices.
Understand and adhere to the Company�s risk and regulatory standards, policies and controls in accordance with the Company�s Risk Appetite. Identify risk-related issues needing escalation to management.
Promote an environment that supports diversity and reflects the Bank brand.
Maintain internal control standards, including timely implementation of internal and external audit points together with any issues raised by external regulators as applicable.
Complete other related duties as assigned.
NATURE AND SCOPE:
MANAGERIAL/SUPERVISORY RESPONSIBILITY:
None

MINIMUM QUALIFICATIONS REQUIRED:
Bachelor�s degree and a minimum of 5 years related experience, or in lieu of a degree, a combined minimum of 9 years higher education and/ or work experience, including a minimum of 5 years related experienceExperience working with multiple statistics and data science principles such as AB testing, sample selection, hypothesis testing, and modeling bias
Proficiency with pertinent statistical software and languages and tools
Experience with various hybrid databases both on premise and in the cloud
Intermediate level knowledge of Structured Query Language (SQL) and Not Only Structured Query Language (nSQL)
Intermediate understanding of modeling techniques such as Bayesian Modeling, Classification models, Cluster analysis, Neural Network, Non-parametric methods, and Multivariate statisticsm
Experience analyzing large data sets
IDEAL QUALIFICATIONS PREFERRED:
Masters� of Science or Doctorate degree in Statistics, Economics, Finance or related field in the quantitative social, physical or engineering sciences, with proven coursework proficiency in statistics, econometrics, economics, computer science, finance or risk management
Fluent in econometric/statistical techniques, including time-series analysis, panel data methods and logistic regression
Tactical experience with pertinent statistical software and languages and tools

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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