We are seeking a highly skilled and motivated individual to join our Data Analytics Team as a Data Scientist with a primary focus on Machine Learning and Tableau. This role combines the responsibilities of both data science and data analytics, requiring a candidate who can extract meaningful insights from complex datasets and guide strategic decisions using advanced data visualization techniques.

Key Responsibilities:

Lead Cross-Functional Projects: Use advanced data modeling and analysis techniques to uncover valuable insights and optimization opportunities.
Develop and Maintain Systems: Build and sustain data models, reporting systems, data automation systems, dashboards, and performance metrics to support crucial business decisions.
Design Data Architectures: Create data models, schemas, and architectures to facilitate seamless data integration, transformation, and analytics processes.
ETL Processes: Develop and manage ETL processes to extract, transform, and load data from various sources into AWS data storage solutions (e.g., Amazon S3, Amazon Redshift) and other SQL-based tools like DBT.
QA Responsibilities: Implement robust data quality and validation processes to ensure data accuracy, consistency, and reliability. Establish and enforce code quality standards for machine learning models developed by junior team members. Review and approve ML pipelines, model training scripts, and production-ready codebases to ensure adherence to software engineering and ML best practices
Building Data Science Models: Develop and deploy data science models to solve complex business problems. Use techniques such as machine learning, predictive modeling, and statistical analysis to drive data-driven decision-making and enhance business outcomes.
In-Depth Analysis: Conduct thorough analysis of large and complex datasets using time series analysis, multivariate techniques, clustering, and unsupervised learning.
Effective Communication: Use Tableau to communicate findings and complex concepts effectively to both technical and non-technical stakeholders.
Oversee Data Requests: Manage the data/report request process, including tracking, prioritization, and approval.
Project Management: Organize and drive the successful completion of data insight initiatives through effective management and collaboration.

Qualifications:

Educational Background: BS degree in Computer Science, Applied Mathematics, Physics, Statistics, Economics, or a related quantitative field.
Relevant Experience: Proven experience as a Data Scientist or a similar role, with a focus on time series analysis, multivariate techniques, unsupervised learning, and decision tree analysis. Demonstrated ability to build and deploy data science models using machine learning, predictive modeling, and statistical analysis to drive business insights and support strategic decision-making.
ML Model Deployment and Version Control: Candidates must have hands-on experience deploying machine learning models to production endpoints (e.g., APIs or cloud services) and managing model versions effectively. Familiarity with Git for version control, including branching and pull requests, is preferred. Candidates should follow best practices to ensure deployments are reproducible, scalable, and maintainable.
ETL Tools Proficiency: Skilled in ETL tools such as Tableau Prep, Alteryx, Informatica, SSIS, Denodo, Fivetran, AWS Glue, Talend, Data Stage, Minitab, SAP Data Services.
Data Visualization: Experience with Tableau or other BI tools for data visualization and insights communication.
SQL Skills: Proficient in SQL with the ability to perform effective querying involving multiple tables and subqueries.
Programming Proficiency: Proficient in programming languages such as Python or R, and experienced with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn).
Work Experience: 2+ years of experience in leadership, management, and team mentoring.
Project Management Skills: Strong ability to plan and manage numerous processes, people, and projects simultaneously.
Communication and Collaboration: Excellent communication, collaboration, and delegation skills.