Own model governance across the portfolio, including documentation, validation artifacts, backtesting, challenger frameworks, and drift monitoring * Partner with Data Engineering to design and ...
Own model governance across the portfolio, including documentation, validation artifacts, backtesting, challenger frameworks, and drift monitoring * Partner with Data Engineering to design and ...
Asset & Wealth Management - Software Engineer - Vice President - Salt Lake City
Salt Lake City, UT · On-site
... backtesting, and production deployment. As a member of this team, you will design and implement the shared infrastructure, libraries, and tooling that power quant workflows across asset classes. The ...
Asset & Wealth Management - Software Engineer - Vice President - Salt Lake City
Salt Lake City, UT · On-site
... backtesting, and production deployment. As a member of this team, you will design and implement the shared infrastructure, libraries, and tooling that power quant workflows across asset classes. The ...
... backtesting, and production deployment. As a member of this team, you will help design and implement the shared infrastructure, libraries, and tooling that powers our Fixed Income trading business.
... backtesting, and production deployment. As a member of this team, you will help design and implement the shared infrastructure, libraries, and tooling that powers our Fixed Income trading business.
Asset & Wealth Management - Software Engineer - Vice President - Salt Lake City
Salt Lake City, UT · On-site
... backtesting, and production deployment. As a member of this team, you will design and implement the shared infrastructure, libraries, and tooling that power quant workflows across asset classes. The ...
Asset & Wealth Management - Software Engineer - Vice President - Salt Lake City
Salt Lake City, UT · On-site
... backtesting, and production deployment. As a member of this team, you will design and implement the shared infrastructure, libraries, and tooling that power quant workflows across asset classes. The ...
... backtesting, and production deployment. As a member of this team, you will help design and implement the shared infrastructure, libraries, and tooling that powers our Fixed Income trading business.
... backtesting, and production deployment. As a member of this team, you will help design and implement the shared infrastructure, libraries, and tooling that powers our Fixed Income trading business.
... backtesting, and production deployment. As a member of this team, you will help design and implement the shared infrastructure, libraries, and tooling that powers our Fixed Income trading business.
... backtesting, and production deployment. As a member of this team, you will help design and implement the shared infrastructure, libraries, and tooling that powers our Fixed Income trading business.
Backtesting information
What are the key skills and qualifications needed to thrive as a Backtesting Analyst, and why are they important?
To thrive as a Backtesting Analyst, you need a strong background in quantitative analysis, statistics, programming (typically in Python or R), and familiarity with financial markets, usually supported by a degree in mathematics, finance, or a related field. Proficiency with backtesting platforms (such as QuantConnect or Zipline), data analysis tools, and version control systems like Git is often required. Attention to detail, critical thinking, and strong problem-solving abilities are key soft skills that help ensure robust model evaluation and development. These skills are vital for accurately assessing trading strategies and minimizing risk in real-world financial applications.
What are some common challenges faced when backtesting trading strategies, and how can they be managed?
One common challenge in backtesting trading strategies is the risk of overfitting, where a model performs exceptionally well on historical data but fails in live markets. Data quality and availability can also pose issues, as incomplete or inaccurate data may skew results. To manage these challenges, it's important to use out-of-sample testing, robust data cleaning processes, and to validate strategies on multiple datasets. Collaborating with quantitative analysts and developers can also help ensure the backtesting process is thorough and reliable.
What is backtesting?
Backtesting is the process of evaluating a trading strategy or investment model by applying it to historical market data. This helps traders and analysts see how the strategy would have performed in the past, which can provide insights into its potential effectiveness and risks. While backtesting can help identify strengths and weaknesses, it's important to remember that past performance is not always indicative of future results. The reliability of backtesting depends on data quality, strategy design, and how well it simulates real trading conditions.
What is the difference between Backtesting vs Quantitative Analyst?
| Aspect | Backtesting | Quantitative Analyst |
|---|---|---|
| Primary Role | Testing trading strategies using historical data | Developing and implementing quantitative models for investment decisions |
| Required Skills | Data analysis, programming, finance knowledge | Mathematics, programming, financial theory |
| Work Environment | Trading firms, hedge funds, financial institutions | Asset management firms, hedge funds, banks |
| Certifications | Often none required, but CFA or CQF helpful | CFA, CQF, or advanced degrees common |
Backtesting focuses on evaluating trading strategies with historical data, while a Quantitative Analyst develops models to inform investment decisions. Both roles require strong analytical skills and finance knowledge but differ in scope and responsibilities.
What are popular job titles related to Backtesting jobs in Utah? For Backtesting jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Backtesting jobs in Utah look for? The top searched job categories for Backtesting jobs in Utah are:
Job description
Established in 2018, Clicklease is dedicated to empowering small business owners frequently overlooked by traditional lenders. Our headquarters are located in the vibrant city of West Valley City, UT, with operations extending to Radial, Alajuela, Costa Rica. We've cultivated a dynamic environment where equipment financing goes beyond being a mere service; it acts as the gateway to realizing entrepreneurial dreams.
Our Core Values:
1. We Are A Happy Company:
At Clicklease, happiness is not just a byproduct; it's a fundamental value. Join a workplace where positivity and joy are cultivated, creating an environment where you can bring your best self to work every day.
2. We Celebrate Collective Intelligence:
We thrive on the brilliance of collaboration. Clicklease is a space where diverse minds come together, combining their intelligence to create solutions that matter. Your ideas are not just heard; they're celebrated.
3. We Practice Empathy:
Empathy isn't just a word in our dictionary; it's a daily practice. Join a team that values understanding and compassion. At Clicklease, we recognize the human side of business and foster a culture where empathy is a guiding principle.
4. We Listen & Learn:
Growth is a continuous journey at Clicklease. We believe in listening and learning from one another. Your insights and experiences contribute to our collective knowledge, making us stronger as a team.
Our Mission:
At Clicklease, we have a clear purpose - to fulfill the capital needs of underserved entrepreneurs and their Main Street Businesses. We achieve this mission through simple, fast, and innovative equipment leasing solutions. This is not just a statement; it's the driving force behind everything we do.
About the role
The Data Science Manager owns the development, deployment, and lifecycle management of Clicklease's credit, fraud, and portfolio models, translating business problems into production-ready modeling solutions that drive measurable risk and financial outcomes.
What you'll be doing:
Essential Functions
Minimum Requirements
Preferred Qualifications
Skills & Competencies
Core Functional Competencies:
Key Technical Skills:
Clicklease only accepts resumes submitted in English
Our Core Values:
1. We Are A Happy Company:
At Clicklease, happiness is not just a byproduct; it's a fundamental value. Join a workplace where positivity and joy are cultivated, creating an environment where you can bring your best self to work every day.
2. We Celebrate Collective Intelligence:
We thrive on the brilliance of collaboration. Clicklease is a space where diverse minds come together, combining their intelligence to create solutions that matter. Your ideas are not just heard; they're celebrated.
3. We Practice Empathy:
Empathy isn't just a word in our dictionary; it's a daily practice. Join a team that values understanding and compassion. At Clicklease, we recognize the human side of business and foster a culture where empathy is a guiding principle.
4. We Listen & Learn:
Growth is a continuous journey at Clicklease. We believe in listening and learning from one another. Your insights and experiences contribute to our collective knowledge, making us stronger as a team.
Our Mission:
At Clicklease, we have a clear purpose - to fulfill the capital needs of underserved entrepreneurs and their Main Street Businesses. We achieve this mission through simple, fast, and innovative equipment leasing solutions. This is not just a statement; it's the driving force behind everything we do.
About the role
The Data Science Manager owns the development, deployment, and lifecycle management of Clicklease's credit, fraud, and portfolio models, translating business problems into production-ready modeling solutions that drive measurable risk and financial outcomes.
What you'll be doing:
- Lead end-to-end development and lifecycle management of credit, fraud, and portfolio models, including PD, LGD, CNL/CGL forecasts, BAV cash flow scoring, fraud/identity scoring, and collections/recovery models
- Serve as hands-on technical lead on the most complex and highest-impact modeling projects, setting standards for experimental rigor, feature engineering, validation methodology, and documentation
- Manage, mentor, and develop the Data Science team, including performance management, coaching, hiring, and prioritization
- Own model governance across the portfolio, including documentation, validation artifacts, backtesting, challenger frameworks, and drift monitoring
- Partner with Data Engineering to design and maintain feature store architecture, training/serving pipelines, and data quality standards
- Translate business questions from Credit Risk, Collections, Finance, Operations, and Sales into well-scoped modeling projects and executive-ready recommendations
- Drive evaluation and adoption of new data sources and modeling techniques to improve decisioning quality
- Ensure compliance with fair lending, ECOA/FCRA, adverse action, and internal model risk standards
Essential Functions
- Design, develop, validate, and deploy predictive models that directly impact credit, fraud, and portfolio performance
- Lead and maintain model governance practices, including monitoring, backtesting, and compliance validation
- Manage and develop team members, including hiring, coaching, and performance evaluation
- Translate complex analytical outputs into actionable business recommendations for senior stakeholders
- Ensure adherence to regulatory requirements, including fair lending and adverse action compliance
- Design and evaluate experimentation frameworks (A/B/C/D tests, pricing tests, strategy rollouts) with proper statistical rigor and causal inference
- Represent the Data Science function in executive and cross-functional forums, translating technical outcomes into business impact
Minimum Requirements
- 7+ years of experience in data science, machine learning, or quantitative modeling
- 2+ years of experience leading projects or mentoring data scientists
- Experience building and deploying production models in a regulated financial services environment
- Experience using Python (pandas, scikit-learn, XGBoost or LightGBM) for model development
- Experience writing and optimizing SQL queries for analytical workflows
- Experience with full model lifecycle including feature engineering, validation, deployment, and monitoring
- Experience presenting analytical findings and recommendations to cross-functional stakeholders
- Bachelor's degree in a quantitative field or equivalent practical experience
Preferred Qualifications
- Experience in consumer, small business, or specialty finance lending
- Familiarity with ECOA, FCRA, Reg B, and fair lending requirements
- Experience with MLOps tooling, feature stores, or model monitoring systems
- Experience with advanced modeling techniques such as survival analysis or causal inference
- Exposure to modern ML tooling or LLM-assisted workflows
Skills & Competencies
Core Functional Competencies:
- Credit and risk modeling expertise
- Model governance and regulatory compliance
- Cross-functional stakeholder alignment
- Team leadership and development
- Experimental design and causal inference
Key Technical Skills:
- Python (pandas, scikit-learn, XGBoost/LightGBM, statsmodels)
- SQL (Snowflake preferred)
- Machine learning model development and validation
- Data pipeline and feature engineering concepts
Clicklease only accepts resumes submitted in English
About Clicklease
Sourced by ZipRecruiter
Industry
Finance and insurance
Company size
11 - 50 Employees
Headquarters location
West Valley City, UT, US
Year founded
2018