R&D Data Scientist: Mathematical Modeling and OptimizationLiftlab Analytics, Inc. • United States
R&D Data Scientist: Mathematical Modeling and Optimization
Liftlab Analytics, Inc.
- United States
- United States
About
Liftlab is the leading provider of science-driven software to optimize marketing spend and predict revenue for optimal spend levels. We call this the Science of Marketing Effectiveness. Our platform combines economic modeling with specialized media experimentation so brands and agencies can clearly see the tradeoffs of growth and profitability. With decades of experience in marketing analytics and data science, our team of industry experts and thought leaders is proud to enable leading and emerging brands such as Cinemark, Express, Hanna Anderson, Lulu & Georgia, Pandora, Sephora, Skims, Tory Burch, Thrive, and Vionic, with our cutting-edge solutions and strategic guidance.
Job responsibilities
Develop new algorithm-based features of LiftLab's marketing measurement and optimization platform Performs diagnostics and root-cause analysis and provide fixes Works with Data Science and Engineering to implement these features into LiftLabs product and workflow Course work/experience:
Data manipulation
SQL Operating on big datasets in Python Data visualization
Mathematical optimization
Linear optimization concepts Nonlinear continuous optimization Linear algebra
Mathematical modeling
Using parametrized systems of equations to represent real-world systems
Statistics
Multivariate regression Clear understanding of Maximum Likelihood estimation and computational methods to find MLE parameters Bayesian concepts Hypotheses testing
Education requirements
Graduate degree in Applied Mathematics, Scientific Computing, Operations Research or related field. We will consider holders of Bachelor degrees with relevant experience
Skills/Aptitude
Engineering and detective mindset
Both to diagnose data and existing algorithms and to develop new analytics functionality
Pragmatic approach to real-world problems Focus on problem solving over applying specific models Willingness to make approximations and assumptions rather than find "the" optimal solution Ability to combine multiple techniques and models to solve end-to end-problems Communication and collaboration skill Ability to convert non-technical requests into project specifications
Languages
- English
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