Data Scientist

DESCRIPTION:

Duties: Collaborate with the business, developers, managers, and other stakeholders to develop and implement the models, deliver the analytics, and integrate the new discoveries into existing models.

Learn quickly about different aspects of the business as well as different modeling methods.

Evaluate and monitor the performance of the new and/or existing models.

Continuously improve the models and automate reports and procedures.

Explore new data, techniques, and environments in order to enhance current models and processes.

Articulate the model results and analytical findings in concise and clear manner using presentations and visualizations.

QUALIFICATIONS:

Minimum education and experience required: Master's degree in Quantitative Finance, Computer Science, Data Science, Statistics, Applied Mathematics, or related field of study plus 3 years of experience in the job offered or as Data Scientist, Analyst, Software Engineer, or related occupation.

Skills Required: This position requires 3 years of experience with the following: building and deploying machine learning models.

This position requires any amount of experience with the following: Xgboost and Random Forest modeling algorithms; building dashboards and alert systems using AWS to provide stakeholders with real-time, data-backed insights for successful feature launches through AB testing; SHAP and model interpretability techniques to enhance understanding of machine learning predictions at an individual level; developing and maintaining data modeling pipelines using AWS Glue and DynamoDB to ensure data accuracy and consistency, performance of data infrastructure, reduce data processing time, and improve decision-making speed; Python including Pandas, Numpy, SKLearn, XGboost libraries, SQL, and PySpark; model evaluation techniques including AUC and Gain Chart; development, implementation, and optimization of machine learning models for market targeting, predictive analysis, customer engagement improvement, increasing campaign effectiveness, and customer behavior forecasting; collaborating with product, engineering, and business teams to define data-driven strategies, design AB tests, and support feature rollouts; supervised and unsupervised modeling techniques including XGboost, Random Forest, Bayesian Parameter Tuning, K-Means, and DBSCAN; Artificial Intelligence and Machine Learning model documentation, development, deployment in marketing, sales, operations, and finance; Python, SQL including Snowflake and SSMS, AWS Glue, and DynamoDB to extract, manipulate, and aggregate data from different data warehouses to solve business problems.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set, and location.

For those in eligible roles, discretionary incentive compensation which may be awarded in recognition of individual achievements and contributions.

We also offer a range of benefits and programs to meet e...