BA or BS degree in statistical analysis, computer science, data science, or related field.
7+ years experience in deploying data science, machine learning, or anomaly detection techniques to solve practical business problems.
Outstanding written and verbal communication, with the ability to make complex data science concepts understandable to non-technical audiences.
Proficiency in SQL, preferably in Snowflake.
Experience with anomaly and outlier detection methods and algorithms.
Strong programming skills in Python with experience using packages such as Pandas, NumPy, scikit-learn.
Experience in quantitative data analysis, possessing a strong ability to conduct in-depth evaluations of complex issues.
Have a creative approach to engineer innovative features and signals into analytical solutions, pushing the boundaries of current tools and methodologies.
Applied knowledge of statistical data analysis to perform trend and anomaly identification, predictive modeling, and hypothesis testing.
Proven ability to make data-driven, convincing arguments to drive process changes.
Demonstrated experience in leading data science projects through all phases including exploratory data analysis, data quality management, modeling, tool deployment, and presentation of results.
Experience with Docker, Kubernetes, Airflow.
Experience with front end libraries such as React or Streamlit.
Experience with LLMs and Graph Databases.
Demonstrated ability to implement, improve, debug, and maintain machine learning models.