Are you interested in applying machine learning or data mining on problems that truly improve people’s life? We’re looking for a mathematician/data scientist eager to tackle unique challenges in the realm of predicting weather’s impact on business. You will work on a skilled team of passionate data scientists and meteorologists. Examples of projects you may encounter would be anything from predicting the electricity output of a solar park in Arizona, to predicting how much ice cream is going to be sold next week in Chicago.
Partner collaboratively with the business and project teams to accomplish tasks/milestones/goals.
Research, recommend, and implement statistical post process correction techniques using proprietary forecasts.
Demonstrate solutions by developing documentation, flowcharts, layouts, diagrams, charts, etc.
Improve operations by conducting systems analysis; recommending changes in policy and procedures.
Provide estimates of work effort and impact of projects and tasks, and provide team leadership, as required.
Continuously build your knowledge by studying new scientific methodologies and techniques.
Play an active role in the product requirements process, giving feedback to product management when challenges arise.
MS in Applied Statistics, Mathematics, Econometrics, or other discipline related to Time-Series Analysis, Machine learning and Forecasting, or other related discipline.
3-5 years of relevant professional experience, with demonstrated achievements.
Can demonstrate mastery of general scientific computing softwares such as R, MATLAB, Octave, etc.
Experience using/implementing non-parametric regression such as Neural Net, SVM, Random Forest, Projection Pursuit, MARS, Radial Basis Functions, AdaBoost, GLM
Experience in Predictive Modeling including Non-Parametric Regression, Bayesian Inference, Hidden Markov Models, Generalized ARMA, or Kalman Filtering is a plus.
Experience in non-linear optimisation including Simulated Annealing, Genetic Algorithm, Agent Based Modeling, Particle Swarm, Bee Colony is a plus but not necessary.
Knowledge of ensemble learning techniques and probabilistic forecasts is a plus.
Programming capabilities including C++, Java, Python is a plus but not necessary.