The organization's data infrastructure needs to be built and developed, and senior leadership requires insights, management reports, and analysis for decision-making processes.
Requirements
- experience using statistics and machine learning to solve complex business problems
- experience conducting statistical analysis with advanced statistical software
- experience scripting languages, and packages
- experience building and deploying predictive models
- experience web scraping, and scalable data pipelines
- experience with big data analysis tools and techniques
- Strong experience with R/RStudio, Python, SAS, SQL, NoSQL
- Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker)
- Strong experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret)
- Strong understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling
Responsibilities
- Performs advanced analytics methods to extract value from business data.
- Performs large-scale experimentation and build data-driven models to answer business questions.
- Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence.
- Determines requirements that will be used to train and evolve deep learning models and algorithms.
- Owns the entire model development process, from identifying the business requirements, data sourcing, model fitting, presenting results, and production scoring.
Other
- Master’s Degree in computer science, statistics, economics or related fields
- 3+ years of work and/or educational experience in machine learning or cloud computing
- Demonstrated ability to communicate complex results to technical and non-technical audiences
- Demonstrated ability to work effectively in teams as well as independently across multiple tasks while meeting aggressive timelines
- Strategic, intellectually curious thinker with focus on outcomes
