4-5 years | Cincinnati, OH
Posted 26 days ago
Do you love discovering insights that drive business value, and transform how work is done? Are you creative, ambitious, and enjoy teaching others about how data science can significantly improve their decision-making?
Your analytic skills are the foundation of this role. The ability to mine mountains of data, derive actionable insights, and then translate those insights into business improving action is essential in our work. You will need to be the primary evangelist to the business for the power of predictive analysis and develop business cases to illustrate the potential for change in decision-making that occurs when you begin to anticipate what will happen, versus just reflecting on what has occurred.
Our leaders are pursuing or have graduated with a Ph.D. in Statistics, Applied Mathematics, Economics, Computer Science, Data Science, Business Analytics, Operation Research, Software Development, or a similar quantitative field. Able to do hands-on mathematical algorithm development as well as programming.
If you are a good fit for the Data Scientist Ph.D. position, you will have:
- Demonstrated leadership in applying and scaling Analytic techniques to be used at an enterprise level.
- Strong written and verbal communication skills to influence others to take action
- Demonstrated ability to handle multiple priorities
- Comfortable working with diverse business scenarios and possessing strong thinking/problem-solving skills that can be applied to business processes with a "can-do" attitude
- Strong enthusiasm and curiosity about the intersection of business and technology
Preferred Specialties/Area of Research:
- Bayesian Analysis, Bayesian Decision Theory
- Probabilistic Modeling and Computation
- Machine Learning, including Deep Learning
- Uncertainty Quantification
- Optimization (global, local, stochastic methods)
- Dynamic (state-space) Models (Kalman Filter, Data Assimilation)
- Experimental Design
- Model Reduction, Dimensionality Reduction
Preferred Experience with Analytical Tools/Applications:
- Big Data Ecosystem: Hadoop, Spark, MapReduce, SQL, Hiv
- Scientific Computing: R, Python, C++, Java, Scala,
- High-Performance Parallel and Distributing Computing
- Deep Learning frameworks: Keras, Tensorflow
- Data Visualization
- Data Management Systems
- Business Intelligence tools: such as KNIME, Tableau
- Industry experience in CPG, Retail preferred. Ability to work across granular retail sales data sets, loyalty/promotional data types also preferred.