QuantLink AI
QuantLink is a financial technology company building data and analytics tools for public equity markets. We use modern software engineering, machine learning, and quantitative research to help investors better understand how companies and stocks have behaved historically under different conditions.
Our platform focuses on:
Organizing and analyzing large sets of technical, fundamental, and price-based data
Providing transparent, evidence-based analytics and tools
Supporting investors and professionals in making more informed, data-driven decisions
As an early-stage company, we work in a focused, collaborative environment where people can take real ownership of their projects and see their work used in production.
Role Overview We are looking for a
Founding Data Scientist
to be one of the earliest technical hires on the team. This is a full-time role based in
Minneapolis, MN , with a
hybrid work arrangement
(a mix of in-office and remote work). You will lead the design, development, and deployment of the core models and analytics that power QuantLink. You’ll work closely with the founders, engineering, and product to define our data science roadmap, evaluate new ideas, and translate research into reliable, production-ready tools.
This role is a good fit for someone who enjoys owning problems end-to-end, from framing the question and exploring data, to building models, shipping them to production, and measuring their impact.
Key Responsibilities
Lead the design and implementation of statistical and machine learning models on large, noisy financial and alternative datasets
Develop and evaluate predictive and descriptive models related to stock behavior and risk/return characteristics
Design, implement, and maintain feature pipelines using technical, fundamental, and price-based data
Build clear, reliable visualizations, dashboards, and analytical tools to communicate insights internally and to end users
Design and run structured evaluations (e.g., backtests, A/B tests, and other experiments) to assess model performance and robustness over time
Work with engineering to bring models into production, including monitoring, diagnostics, and iteration
Partner with product and founders to identify high-impact questions, prioritize work, and shape the overall data science roadmap
Establish best practices for data quality, documentation, experiment design, and reproducibility
Mentor future data science hires as the team grows and contribute to building a strong technical culture
Required Qualifications
4+ years of experience in
Data Science, Machine Learning, or Quantitative Research , including building models that have been used in real products or decisions
Strong proficiency in
Statistics , including:
Regression and generalized linear models
Distributions, uncertainty, and inference
Hypothesis testing and experiment design
Advanced
analytical and problem-solving skills , with a track record of framing ambiguous problems and driving them to conclusions
Proficiency in
Python
(e.g., pandas, NumPy, scikit-learn or similar) and experience writing production-quality code
Working knowledge of
SQL
and experience working with relational databases and large datasets
Practical experience with
machine learning techniques , such as:
Linear and logistic regression
Tree-based models and ensembles
Clustering and dimensionality reduction
Time-series modeling concepts
Experience building and using
data visualization
and reporting tools (e.g., Matplotlib, Plotly, Tableau, Power BI, or similar)
Experience taking models or data products from prototype to production in partnership with engineers
Ability to
work collaboratively
in a small, fast-paced team and to communicate clearly with both technical and non-technical stakeholders
Comfort working in an early-stage startup environment with evolving priorities and a high degree of ownership
Nice to Have
Experience with
financial markets, equity research, portfolio analytics, or trading systems
Hands-on experience with
time-series modeling , including forecasting and evaluation in live or semi-live settings
Experience with
cloud platforms
(AWS, GCP, or Azure) and modern data tooling (e.g., dbt, Airflow, Spark, Ray, or similar)
Previous experience at an early-stage startup or in building a new data science function or product from the ground up
Experience with
MLOps
practices (monitoring, retraining, model versioning)
Graduate degree in a quantitative field (e.g., Statistics, Computer Science, Mathematics, Physics, Engineering, or similar), or equivalent practical experience
Why QuantLink?
Work on real-world problems where your code ships to production and is used by actual users
Get exposure to the full lifecycle of building a data product, including design, implementation, testing, deployment, and monitoring
Collaborate closely with data science and research teammates and see how software engineering connects to quantitative analytics and decision-making
Learn directly from experienced founders and technical leaders in software, data, and product
Join early enough to have meaningful ownership over projects, tools, and processes, and to influence the direction of the product and engineering stack
Seniority level Mid-Senior level
Employment type Full-time
Job function Engineering and Information Technology
Industries Technology, Information and Internet
Location and Salary Minneapolis, MN – $80,070.00 – $143,208.00
#J-18808-Ljbffr
Our platform focuses on:
Organizing and analyzing large sets of technical, fundamental, and price-based data
Providing transparent, evidence-based analytics and tools
Supporting investors and professionals in making more informed, data-driven decisions
As an early-stage company, we work in a focused, collaborative environment where people can take real ownership of their projects and see their work used in production.
Role Overview We are looking for a
Founding Data Scientist
to be one of the earliest technical hires on the team. This is a full-time role based in
Minneapolis, MN , with a
hybrid work arrangement
(a mix of in-office and remote work). You will lead the design, development, and deployment of the core models and analytics that power QuantLink. You’ll work closely with the founders, engineering, and product to define our data science roadmap, evaluate new ideas, and translate research into reliable, production-ready tools.
This role is a good fit for someone who enjoys owning problems end-to-end, from framing the question and exploring data, to building models, shipping them to production, and measuring their impact.
Key Responsibilities
Lead the design and implementation of statistical and machine learning models on large, noisy financial and alternative datasets
Develop and evaluate predictive and descriptive models related to stock behavior and risk/return characteristics
Design, implement, and maintain feature pipelines using technical, fundamental, and price-based data
Build clear, reliable visualizations, dashboards, and analytical tools to communicate insights internally and to end users
Design and run structured evaluations (e.g., backtests, A/B tests, and other experiments) to assess model performance and robustness over time
Work with engineering to bring models into production, including monitoring, diagnostics, and iteration
Partner with product and founders to identify high-impact questions, prioritize work, and shape the overall data science roadmap
Establish best practices for data quality, documentation, experiment design, and reproducibility
Mentor future data science hires as the team grows and contribute to building a strong technical culture
Required Qualifications
4+ years of experience in
Data Science, Machine Learning, or Quantitative Research , including building models that have been used in real products or decisions
Strong proficiency in
Statistics , including:
Regression and generalized linear models
Distributions, uncertainty, and inference
Hypothesis testing and experiment design
Advanced
analytical and problem-solving skills , with a track record of framing ambiguous problems and driving them to conclusions
Proficiency in
Python
(e.g., pandas, NumPy, scikit-learn or similar) and experience writing production-quality code
Working knowledge of
SQL
and experience working with relational databases and large datasets
Practical experience with
machine learning techniques , such as:
Linear and logistic regression
Tree-based models and ensembles
Clustering and dimensionality reduction
Time-series modeling concepts
Experience building and using
data visualization
and reporting tools (e.g., Matplotlib, Plotly, Tableau, Power BI, or similar)
Experience taking models or data products from prototype to production in partnership with engineers
Ability to
work collaboratively
in a small, fast-paced team and to communicate clearly with both technical and non-technical stakeholders
Comfort working in an early-stage startup environment with evolving priorities and a high degree of ownership
Nice to Have
Experience with
financial markets, equity research, portfolio analytics, or trading systems
Hands-on experience with
time-series modeling , including forecasting and evaluation in live or semi-live settings
Experience with
cloud platforms
(AWS, GCP, or Azure) and modern data tooling (e.g., dbt, Airflow, Spark, Ray, or similar)
Previous experience at an early-stage startup or in building a new data science function or product from the ground up
Experience with
MLOps
practices (monitoring, retraining, model versioning)
Graduate degree in a quantitative field (e.g., Statistics, Computer Science, Mathematics, Physics, Engineering, or similar), or equivalent practical experience
Why QuantLink?
Work on real-world problems where your code ships to production and is used by actual users
Get exposure to the full lifecycle of building a data product, including design, implementation, testing, deployment, and monitoring
Collaborate closely with data science and research teammates and see how software engineering connects to quantitative analytics and decision-making
Learn directly from experienced founders and technical leaders in software, data, and product
Join early enough to have meaningful ownership over projects, tools, and processes, and to influence the direction of the product and engineering stack
Seniority level Mid-Senior level
Employment type Full-time
Job function Engineering and Information Technology
Industries Technology, Information and Internet
Location and Salary Minneapolis, MN – $80,070.00 – $143,208.00
#J-18808-Ljbffr