

Senior Data Scientist for B2B Strategic Partnership - CBOT Seat Sublease
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist focusing on B2B Strategic Partnerships, offering a contract lasting over 6 months, with a pay rate of $50,895.78 to $2,000,000.00 per year. Key skills include regression modeling, calculus, and ETL processes.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
9090.9090909091
-
ποΈ - Date discovered
September 23, 2025
π - Project duration
More than 6 months
-
ποΈ - Location type
Remote
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π - Contract type
Unknown
-
π - Security clearance
Unknown
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π - Location detailed
Remote
-
π§ - Skills detailed
#SciPy #Calculus #Monitoring #Data Science #API (Application Programming Interface) #Regression #Documentation #"ETL (Extract #Transform #Load)" #Data Integrity
Role description
Overview
Small manufacturing firm seeks math geek to assist with cleaning up futures arbitrage algorithm and monitoring in the course of 23/6 CME GlobeX sessions. You'll be responsible for sprinting through app cleanup, effectuating client-side KPI derivations, fitting spline regression models, applying cross-validation, deploying mean reversion to smooth a yield curve, using linear algebra to solve systems of equations, and overseeing process improvements.
Duties
Script ETL Processes.
Navigate API documentation.
Apply calculus to derive KPIs from immutable observable variables.
Develop smoothing and penalty functions to optimize chi-squared values.
Use Cross Validation to improve goodness of fit.
Integrate recent observations into an adaptive ARIMA.
Penalize datas with partial stochastic differentials.
Solve big systems with advanced algebras.
Use systems of equations to select combinations that minimize a given objective function.
Applying thread locking and similar concepts to ensure data integrity.
Requirements
Proven experience as a mathematician and data scientist.
Knowledge of analytics tools and techniques.
Familiarity with regression modeling tools like StatsModels and SciPy.
Skills designing experiments and evaluating hypotheses.
Knowledge of data warehousing concepts is a plus.
Ok with revenue share/seat lease agreement in lieu of traditional salary. This does require you to commit some cash or credit.
Please send your resume if interested. If you have appropriate qualifications we will schedule an interview.
Job Type: Contract
Pay: $50,895.78 - $2,000,000.00 per year
Work Location: Remote
Overview
Small manufacturing firm seeks math geek to assist with cleaning up futures arbitrage algorithm and monitoring in the course of 23/6 CME GlobeX sessions. You'll be responsible for sprinting through app cleanup, effectuating client-side KPI derivations, fitting spline regression models, applying cross-validation, deploying mean reversion to smooth a yield curve, using linear algebra to solve systems of equations, and overseeing process improvements.
Duties
Script ETL Processes.
Navigate API documentation.
Apply calculus to derive KPIs from immutable observable variables.
Develop smoothing and penalty functions to optimize chi-squared values.
Use Cross Validation to improve goodness of fit.
Integrate recent observations into an adaptive ARIMA.
Penalize datas with partial stochastic differentials.
Solve big systems with advanced algebras.
Use systems of equations to select combinations that minimize a given objective function.
Applying thread locking and similar concepts to ensure data integrity.
Requirements
Proven experience as a mathematician and data scientist.
Knowledge of analytics tools and techniques.
Familiarity with regression modeling tools like StatsModels and SciPy.
Skills designing experiments and evaluating hypotheses.
Knowledge of data warehousing concepts is a plus.
Ok with revenue share/seat lease agreement in lieu of traditional salary. This does require you to commit some cash or credit.
Please send your resume if interested. If you have appropriate qualifications we will schedule an interview.
Job Type: Contract
Pay: $50,895.78 - $2,000,000.00 per year
Work Location: Remote