The Role
Develop and productionize statistical, econometric, and machine learning models using large, complex datasets. Lead data sourcing, ingestion, cleaning, drift monitoring, model refinement, and self-healing model frameworks. Create model outputs for business stakeholders, review code, support research approaches, and mentor less experienced team members. Ensure adherence to risk, regulatory, audit, and internal control standards.
Summary Generated by Built In
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
Skills Required
- Bachelor's degree and at least 5 years of related experience, or 9 years of combined higher education and work experience including 5 years of related experience
- Experience applying statistical and data science principles, including A/B testing, sample selection, hypothesis testing, and modeling bias
- Proficiency with relevant statistical software, programming languages, and tools
- Experience with hybrid databases in on-premise and cloud environments
- Intermediate knowledge of SQL and NoSQL
- Intermediate understanding of Bayesian modeling, classification, cluster analysis, neural networks, non-parametric methods, and multivariate statistics
- Experience analyzing large datasets
- Master's or doctoral degree in statistics, economics, finance, or a related quantitative discipline
- Coursework proficiency in statistics, econometrics, economics, computer science, finance, or risk management
- Fluency in econometric and statistical techniques, including time-series analysis, panel data methods, and logistic regression
- Practical experience with relevant statistical software, programming languages, and tools
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The Company
What We Do
CTI Consulting is a South Florida technology solutions and staffing firm founded in 1998. It provides IT staffing and nearshore staffing services for startups through Fortune 100 companies, alongside digital-product work such as designing, testing, deploying, improving, and updating mobile applications. The company emphasizes close client collaboration, comprehensive candidate evaluation, continuing education, and innovative, scalable software solutions that improve operational efficiency.
