Project Manager

About the Role

Key Responsibilities

• Develop predictive models using statistical algorithms and machine learning techniques.
• Analyze data quality and ensure data integrity using statistical procedures.
• Create project plans, team structures, milestones, and project deliverables.
• Identify tools for data ingestion and storage, and set up data-labs and analytical workspaces.
• Work on real-time data capture and provide platform support for real-time analytics.
• Build data frameworks in HIVE, PySpark, Scala, and Amazon Redshift for data pipeline development.
• Automate and standardize development and testing processes using ETL tools and frameworks.
• Process, clean, and transform data to ensure it is in the desired format for analysis.
• Create, merge, and manipulate data tables using SQL, and create flags as needed.
• Validate and ensure the performance and robustness of data models, including prediction accuracy.
• Optimize models through feature engineering, variable selection, and hyperparameter tuning.
• Analyze online behavior, interpret business needs, and outline project scope based on client requirements.
• Share insights and provide recommendations to clients and stakeholders.
• Present data analysis results and strategic insights to leadership and stakeholders.
• Create visualizations, dashboards, and automated reports for data presentation.
• Ensure code integration and deployment (CI/CD) linked to SDLC metrics.

Requirements

• Requires Master's degree, or foreign equivalent, in Operations Research, Computer Science, Information Systems, or a related field, plus one (1) year of experience in Statistician or related occupation.
• Requires 1 year of professional experience in data extraction and data visualization.
• Experience with Python and R.
• Experience with Agile project management methodology.
• Experience working with complex data structures and large datasets in a real business setting.
• Experience developing end-to-end solutions from requirement gathering to deployment and building key business metrics.
• Proficiency with Business Intelligence (BI) tools including Excel or Tableau.
• Proficiency with analytical tools including SAS and SQL.
• Experience building, validating, and monitoring statistical models to meet client guidelines.
• Experience delivering data analytics presentations to clients, senior managers, and executives.

Nice to Have

• Experience with Qubole and Snowflake for data workspace setup.
• Experience with data pipeline development and SDLC processes.
• Knowledge of hyperparameter tuning and feature engineering techniques.

Qualifications

• Master's degree in relevant field plus one year of experience, or Bachelor's degree plus three years of experience in a related field.

Benefits & Perks

• Salary of $142,000 - $145,000 per year.
• Work hours from 9:00am to 5:00pm, 40 hours/week.
• Telecommuting permitted from anywhere in the United States.