Data Scientist

Data Architect - Mid-LevelLocation: Framingham, MAOnsite Flexibility: OnsiteContract DetailsPosition Type: ContractContract Duration: 14 monthsPay Rate: $60.00–$80.00 / Hour (USD)Contract-to-Hire: Contract-to-hire potentialInterview 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 (e.g., GitHub).Work Authorization: Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.Job SummaryThe 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.Key ResponsibilitiesDesign, develop, and deploy machine learning models and statistical algorithms to solve complex business and IT problemsAnalyze large, structured and unstructured datasets to extract meaningful insights and drive data-informed decisionsBuild, maintain, and run automated and ad-hoc reports to support business operations and strategic initiativesCollaborate with cross-functional teams to identify opportunities for leveraging data and fulfill ad-hoc data requests to support timely and informed decision-makingBuild and maintain data pipelines and workflows to support scalable analytics, reporting, and model deploymentCommunicate technical findings and recommendations clearly to both technical and non-technical stakeholdersConduct Time-Series, Sequential testing and other experimental designs to evaluate the impact of business and IT initiativesProvide guidance on technical approaches and best practicesRequired SkillsProficiency in Python, SQL, Unix Shell Scripting (Linux Shell Scripting), and Stored ProceduresExperience 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 pipelinesStrong problem-solving skills, attention to detail, and ability to work independently and collaborativelyHighly developed verbal and written communication skills, with the ability to work up and down within the organization to influence others and achieve resultsPreferred SkillsProven application of advanced techniques in a business setting with impactful resultsCI/CD platforms (Jenkins, GitHub, Control-M)Familiarity with data visualization tools such as Tableau and Power BIExperience designing and evaluating experiments, including A/B testing and other statistical test methodologiesExperience with time series modeling techniques and/or product recommendation systemsFamiliarity with data ingestion, transformation, and integrationEducation RequirementsA degree in a quantitative field such as Data Science, Computer Science, Engineering, or Mathematics (preferred)Required Experience5–10 years of professional experience in a data analytics or related roleBenefitsMedical, Vision, and Dental Insurance Plans401k Retirement FundAbout the ClientThis client is a Fortune 100 retailer and the world's leading off-price apparel and home fashions company, operating more than 5,200 stores across ten countries under iconic retail brands including TJ Maxx, Marshalls, HomeGoods, Homesense, and Sierra in the United States; Winners, HomeSense, and Marshalls in Canada; and TK Maxx and Homesense across Europe and Australia. Built on a business model that delivers quality, brand-name, and designer merchandise at prices typically 20 to 60 percent below full-price retail, the organization has created one of the most distinctive and enduring value propositions in global retail. The company's product assortment spans apparel, footwear, accessories, home décor, furniture, giftware, jewelry, and more — curated through a dynamic buying strategy that keeps merchandise fresh and store visits exciting. Customers return repeatedly because they know that each visit may surface something unexpected — a core feature of the off-price retail model that this company has perfected over decades. Internally, the organization is known for offering a fast-paced, entrepreneurial environment where buyers, merchants, and retail professionals gain hands-on experience across a broad range of disciplines. The company's scale — combined with its global footprint — creates meaningful career pathways for motivated individuals in merchandising, operations, supply chain, corporate finance, marketing, and technology, including data scientists, data architects, software engineers, and analytics professionals who collaborate across the enterprise. For professionals who thrive in dynamic, commercially driven environments and want to work within a globally recognized retail brand with real market leadership and substantial career development opportunities, this is an organization worth serious consideration.About GTTGTT is a minority-owned staffing firm and a subsidiary of Chenega Corporation, a Native American-owned company in Alaska. We highly value diverse and inclusive workplaces and support Fortune 500 organizations across banking, financial services, technology, life sciences, biotech, utilities, and retail sectors throughout the U.S. and Canada.