Data Scientist Jobs

About The Position

Requirements

• Master’s degree or equivalent in Computer Science, Statistics, Engineering (any), or a related field plus 1 year of experience in analytics or a related field; OR bachelor’s degree or equivalent in one of these fields plus 3 years of experience in analytics or a related field.
• Experience coding in object-oriented programming languages, specifically Python.
• Experience applying statistical techniques such as probability, hypothesis testing, and regression analysis.
• Experience applying supervised, unsupervised, and semi-supervised machine-learning techniques, including linear and logistic regression, decision trees, support vector machines, and deep learning models using PyTorch, TensorFlow, and Keras.
• Experience building optimization models and solving them using integer programming or linear programming.
• Experience creating clear and informative data visualizations using Seaborn and MATLAB plot.
• Experience writing SQL queries.
• Experience working with large datasets using languages such as PySpark.
• Experience running experiments scientifically and analyzing experiment results.
• Employer will accept any amount of graduate coursework, graduate research experience, or professional experience with the required skills.

Responsibilities

• Select appropriate analytical modeling techniques for structured and complex datasets and develop customized analytical models.
• Conduct exploratory data analysis, statistical analysis, hypothesis testing, and statistical inference.
• Define and refine features based on model performance, introducing new or revised features to improve analytical outcomes.
• Design experiments by identifying key dimensions, finalizing experimental design, testing hypotheses, and executing analyses.
• Perform trend and cluster analyses to address business problems and deliver actionable insights and recommendations.
• Apply model fit testing, tuning, and validation techniques, and select evaluation metrics based on model objectives and business requirements.
• Assess the impact of variables and features on model performance and evaluate model accuracy, fit, validity, and robustness across multi-stage models and model ensembles.
• Support production deployment and operational sustainability of analytical models, including model evaluation, scalability, and long-term maintenance.
• Develop required solutions and application features using programming languages and knowledge of business and domain requirements.
• Apply static testing, dynamic testing, software composition analysis, and manual penetration testing to ensure code quality, functionality, and security.

Benefits

• Competitive pay and performance-based incentive awards, including annual or quarterly performance incentives.
• Medical, vision, and dental coverage.
• 401(k), stock purchase, and company-paid life insurance.
• Paid time off, including sick leave, parental leave, family care leave, bereavement leave, jury duty, and voting leave.
• Short-term and long-term disability.
• Education assistance, including 100% company-paid college degrees.
• Company discounts.
• Military service pay.
• Adoption expense reimbursement.