Job Duties / Responsibilities
- Ingest, organize, and analyze data from various sources (e.g. CSV, relational database)
- Scope unstructured problems or messy data for tractable insights
- Identify candidate statistical or machine learning solutions and test their efficacy
- Communicate technical work and findings both verbally and through written reports and visualizations
- Lead discussions and assess the feasibility of AI / ML solutions for business processes and outcomes
- Work in a collaborative environment to brainstorm, design, implement and deliver solutions to challenging problems
- Create comprehensive analytical solutions, from data gathering to display; assist in the construction of data engineering pipelines
Qualifications and Skills
5 Years or more of relevant industry work experienceExcellent understanding of statistical or machine learning techniques, such as clustering, regression, time series forecasting, tree-based methods, sampling methodsDemonstrated ability using scientific computing libraries, such as NumPy, Pandas, SciPy, Scikit-learn, Matplotlib, and PlotlyProgramming proficiency in Python or RExperience in database interrogation and analysis tools, such as Hadoop, SQL and SparkStrong oral and verbal communication and presentation skillsPreferred Requirements
Master’s or PhD degree in a quantitative disciplineStrong statistical knowledge and experience with hypothesis testingFluency with machine learning algorithms, such as CNN, RNN, reinforcement learning, support vector machines, and graph-based modelsExperience with TensorFlow, Keras, or PyTorchExperience with version control systems (e.g. Git flow)Experience working on AWS or Azure cloud based data science tools (e.g. SageMaker, Databricks)Familiarity with BI and AI tools such as Tableau and DataikuResearch experience with high impact publicationsExperience working with cross-functional teams and / or customer facing work