Data Architect - Mid-Level

Data Scientist Framingham, MA 12 month+ contract Only no C2C(No H1b or opt) Please note: Looking for 5-10 years of experience. Not considering senior candidate • Interview process: expected to be 2 -3 rounds; last round could be with one person; there could be a technical assessment • Include candidate project portfolio if applicable (example GitHub) Job Descriptions The Merchandise Operations Management Delivery team is responsible for modernization of Global Merchandise Financial systems, as well as our Pricing and Clearance Management systems. We achieve these goals by implementing off-the-shelf solutions (Oracle Retail), which drive the ability to support key finance processes and markdown strategies. Our business customers rely on the accuracy and integrity of the solutions we provide to manage our merchandise, pay our vendors accurately and in a timely fashion and ultimately report accurate data to Wall Street. As a Data Scientist, you'll be part of a dynamic and collaborative environment that touches every aspect of the business—from product placement and inventory optimization to systems engineering analytics and modeling. You'll work closely with cross-functional partners across product, engineering, and merchandising, providing both strategic insights and ad-hoc data support to fuel smarter decisions. Your Impact • Design, develop, and deploy machine learning models and statistical algorithms to solve complex business and IT problems • Analyze large, structured and unstructured datasets to extract meaningful insights and drive data-informed decisions • Build, maintain, and run automated and ad-hoc reports to support business operations and strategic initiatives • Collaborate with cross-functional teams to identify opportunities for leveraging data and fulfill ad-hoc data requests to support timely and informed decision-making • Build and maintain data pipelines and workflows to support scalable analytics, reporting, and model deployment • Communicate technical findings and recommendations clearly to both technical and non-technical stakeholders • Conduct Time-Series, Sequential testing and other experimental designs to evaluate the impact of business and IT initiatives • Provides guidance on technical approaches, and best practices Required Qualifications • 5-10 years of professional experience in a data analytics or related role. • Proficiency in Python, SQL, Unix Shell Scripting (Lunex Shell Scripting), Stored Procedures. • Experience with one OR more machine learning frameworks and data analysis/visualization libraries in Python (e.g. Pandas, scikit-learn, PyTorch, Matplotlib, Plotly, etc.) • ETL tool experience (Talend, DataStage, or MoveIT Automation preferred) • EDW/ DB experience (Snowflake OR Oracle databases preferred) • Experience with CI/CD pipelines • Strong problem-solving skills, attention to detail, and ability to work independently and collaboratively • Highly developed verbal and written communication skills, with the ability to work up and down within the organization to influence others and achieve results Preferred Qualifications • A degree in a quantitative field such as Data Science, Computer Science, Engineering or Mathematics • Proven application of advanced techniques in a business setting with impactful results • CI/CD platforms (Jenkins, GitHub, Control-M) • Familiarity with data visualization tools such as Tableau and Power BI • Experience designing and evaluating experiments, including A/B testing and other statistical test methodologies • Experience with time series modeling techniques and/or product recommendation systems • Familiarity with data ingestion, transformation, and integration Job #: 25-46805