Overview
On Site
Full Time
Skills
Mergers and Acquisitions
Operations Management
Financial Software
Pricing
Security Clearance
Oracle Retail
Finance
Management
Inventory Optimization
Systems Engineering
Product Engineering
Merchandising
Algorithms
Business Operations
Collaboration
Decision-making
Workflow
Analytics
Reporting
Testing
SQL
Unix
Shell Scripting
Stored Procedures
Machine Learning (ML)
Data Analysis
Visualization
Python
Pandas
scikit-learn
PyTorch
matplotlib
Plotly
Extract
Transform
Load
Talend
IBM InfoSphere DataStage
Datastage
Data Warehouse
Snow Flake Schema
Oracle
Database
Conflict Resolution
Problem Solving
Attention To Detail
Communication
Data Science
Computer Science
Mathematics
Continuous Integration
Continuous Delivery
Jenkins
GitHub
BMC Control-M
Data Visualization
Tableau
Microsoft Power BI
A/B Testing
Test Methods
Time Series
Modeling
Job Details
Data Scientist
Framingham, MA
12 month+ contract
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
Framingham, MA
12 month+ contract
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
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.