The Simulation Scientist develops and maintains simulation algorithms applied to econometric and parameter estimation problems. The candidate must be adept with MCMC methods and should be familiar with their application to marketing problems including hierarchical models. Experience with market basket modeling is a big plus. The candidate should also be able to apply other techniques to problems where simulation is not appropriate.
Science is a key differentiator at DecisionNext. The Scientist’s primary role is to develop algorithms in an area of core expertise. Scientists must also be able to develop and maintain computer code that expresses designs within real life product implementations. Candidates must be able to explain their work clearly to non-specialists including customers and colleagues, and they must excel in both written and spoken communication. Professional software development standards and methods are expected of all members of the team. Strong skills in Unix and Python are appreciated. Science team members typically have a PhD in Operations Research, Physics, Applied Math, Statistics, or a related field. New team members will usually have completed a postdoc or similar industry experience, but fresh PhDs or Masters plus several years of related industry experience may also be considered.
Desired Skills and Experience
- MCMC, Bayesian inference, hierarchical models.
- PhD in Operations Research, Physics, Applied Math, Statistics, or a related field.
- Strong programming skills, particularly in Python on a Linux platform.
- Strong communication skills.
- Background in optimization, marketing science, or commodities helpful.
DecisionNext is a new company with a big development agenda. We are a SaaS analytics company helping customers in multiple industries make high-value decisions across the enterprise. We optimize a company’s end-to-end performance by linking supply markets to demand markets through analytical frameworks and applications. Our products influence purchasing, selling and operational decisions by analyzing, understanding and balancing key information flows and demand factors.
DecisionNext offers the ground floor opportunity and excitement of an early stage startup but with established contracts and development plans of a mature company. The founders have an extensive track record in the space of optimization and predictive analytics. We are looking for talented scientists and engineers to help us build next generation analytical software in a flexible and congenial startup atmosphere. DecisionNext is an equal opportunity employer based in San Francisco. Candidates must be local or able to relocate.
If interested please send your resumé and cover letter to Ryan MacDonald at email@example.com