Bachelor's Degree in Computer Science, Statistics, Mathematics, Engineering or a related field is required. Master's Degree in a quantitative or a related field is highly preferred.
Knowledge of data analytics tools for data pipelines, cloud storages (AWS), and Hands-on experience with designing and developing dashboards using self-service analytics tools
Ability to leverage multiple tools and programming languages to aggregate, standardize, analyze, interpret and manipulate large data sets from disparate data sources or within a data warehouse or decentralized environment.
Proficiency in Python, including Pandas, NumPy
At least one Python data visualization library (e.g. Matplotlib, Seaborn)
At least one Python ML library (e.g. Scikit-learn, TensorFlow)
Visualization platforms: Power BI and Tableau
Experience working in Git
3 years of relevant experience with data tools, techniques, and manipulation preferred.
Statistical modelling experience including: GBM, linear and logistic regression, decision tree, and propensity scoring and other advanced quantitative techniques.
Excellent written and verbal communication skills, including the ability to convey complex ideas clearly and to communicate with both technical and nontechnical audiences