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.