R&D Data Scientist: Modeling & Optimization

Liftlab Analytics, Inc.; United States; Remote; USD 120,000 - 170,000; Full time

Job summary

Liftlab is seeking a highly mathematical data scientist to build algorithm-based features for its marketing measurement platform. You will work with Data Science and Engineering to deploy analytics into product, perform diagnostics, and manipulate large datasets with Python and SQL.

The ideal candidate holds a graduate degree in Applied Mathematics, Scientific Computing, OR, or a related field (Bachelor with experience considered).

Qualifications

• Graduate degree in Applied Mathematics, Scientific Computing, Operations Research or related field.
• Bachelor degree with relevant experience considered for similar roles.
• Engineering and detective mindset to diagnose data and algorithms.

Responsibilities

• Develop new algorithm-based features of LiftLab’s marketing measurement and optimization platform.
• Performs diagnostics and root-cause analysis and provide fixes.
• Collaborates with Data Science and Engineering to deploy features into LiftLab’s product and workflow.
• Data manipulation.
• SQL.
• Operating on big datasets in Python.
• Mathematical optimization.
• Nonlinear continuous optimization.
• Mathematical modeling.
• Using parametrized systems of equations to represent real-world systems.
• Statistics.
• Multivariate regression.
• MLE parameters estimation.

Skills

SQL

Python

Multivariate regression

MLE

Bayesian statistics

Hypotheses testing

Mathematical optimization

Mathematical modeling

Data manipulation

Education

Graduate degree in Applied Mathematics, Scientific Computing, Operations Research or related field

Bachelor degree with relevant experience

Job description

Liftlab is seeking a highly mathematical data scientist to build algorithm-based features for its marketing measurement platform. You will work with Data Science and Engineering to deploy analytics into product, perform diagnostics, and manipulate large datasets with Python and SQL.

The ideal candidate holds a graduate degree in Applied Mathematics, Scientific Computing, OR, or a related field (Bachelor with experience considered).