

SGS
Data Scientist
β - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Scientist contract position for 40 hours per week, paying $45.00 - $51.00 per hour. Requires 5+ years in Data Science, strong Python and SQL skills, MLOps experience, and expertise in cloud platforms. Retail experience preferred. Hybrid work location.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
408
-
ποΈ - Date
January 8, 2026
π - Duration
Unknown
-
ποΈ - Location
Hybrid
-
π - Contract
Unknown
-
π - Security
Unknown
-
π - Location detailed
Conshohocken, PA 19428
-
π§ - Skills detailed
#Supervised Learning #Deep Learning #"ETL (Extract #Transform #Load)" #TensorFlow #DevOps #BERT #Cloud #Python #Knowledge Graph #MLflow #SQL (Structured Query Language) #Data Engineering #GCP (Google Cloud Platform) #BI (Business Intelligence) #Data Pipeline #A/B Testing #Unsupervised Learning #Customer Segmentation #Visualization #Airflow #Computer Science #PyTorch #Statistics #Data Science #Automation #Model Deployment #SQL Queries #Monitoring #AI (Artificial Intelligence) #Agile #Classification #AWS (Amazon Web Services) #Scala #Mathematics #Deployment #ML (Machine Learning) #Neural Networks
Role description
Job type β IT
Weekly day range
β’ : Hybrid 3 days onsite 2 days remote.
Required :
5+ years of experience in Data Science, Machine Learning, or related fields.
Strong expertise in Python, SQL, and modern ML frameworks (TensorFlow, PyTorch, Scikit-Learn).
Experience with MLOps tools (MLflow, Kubeflow, Airflow) for model deployment and monitoring.
Proficiency in cloud platforms (AWS/GCP) and scalable data engineering.
Strong understanding of probability theory, statistics, and experimental design (A/B Testing).
Experience with collaborative software engineering practices (Agile, DevOps).
Job Summary :
We are seeking a highly skilled Data Scientist to drive the adoption of algorithmic decision-making at scale within Group Digital. This role will focus on developing and deploying machine learning models and neural networks, supporting MLOps practices, to enhance personalization and automation within our digital products. You will work closely with data engineers, product teams, and business stakeholders to build scalable data pipelines, CI/CD workflows, and ETL processes. The ideal candidate will have experience in retail, personalization, web technologies, and cutting-edge AI methods, including Large Language Models (LLMs), Generative AI, and Knowledge Graphs.
Key Responsibilities :
Machine Learning & AI Development
Develop and optimize predictive and prescriptive models to extract insights and enhance decision-making. Knowledgeable in supervised and unsupervised learning. Apply deep learning and neural network techniques for customer classification and profiling, customer segmentation, and personalization.
Utilize MLOps to efficiently deploy, monitor, and maintain ML models in production.
Implement and fine-tune Large Language Models (LLMs) and Generative AI solutions for automation and user engagement.
Explore and integrate knowledge graphs to enhance data relationships and improve AI-driven recommendations.
Data Engineering & Pipelines
Work with data engineers to design and develop robust data pipelines for large-scale ETL processing using SQL and cloud-based solutions (GCP preferred).
Write complex SQL queries for extracting, transforming, and loading (ETL) data efficiently. Implement CI/CD workflows to automate model training, deployment, and monitoring. Collaboration & Agile Development
Work in an Agile/DevOps environment, collaborating with cross-functional teams to drive data-driven innovation.
Promote a data-centric culture by educating teams on the strategic importance of AI and analytics.
Clearly communicate complex methodologies, results, and business insights to both technical and non-technical audiences.
Preferred Qualifications
Experience with Knowledge Graphs and their integration into AI/ML pipelines.
Hands-on experience in LLMs (e.g., GPT, BERT, LLaMA, Claude) and Generative AI technologies.
Background in Retail and Personalization Web Technologies.
Understanding of digital ecosystem and data-driven decision-making.
Proficiency in business intelligence (BI) tools and data visualization.
Education:
Bachelor's or Masterβs degree in Computer Science, Mathematics, Engineering, or related field.
Job Type: Contract
Pay: $45.00 - $51.00 per hour
Expected hours: 40 per week
Work Location: In person
Job type β IT
Weekly day range
β’ : Hybrid 3 days onsite 2 days remote.
Required :
5+ years of experience in Data Science, Machine Learning, or related fields.
Strong expertise in Python, SQL, and modern ML frameworks (TensorFlow, PyTorch, Scikit-Learn).
Experience with MLOps tools (MLflow, Kubeflow, Airflow) for model deployment and monitoring.
Proficiency in cloud platforms (AWS/GCP) and scalable data engineering.
Strong understanding of probability theory, statistics, and experimental design (A/B Testing).
Experience with collaborative software engineering practices (Agile, DevOps).
Job Summary :
We are seeking a highly skilled Data Scientist to drive the adoption of algorithmic decision-making at scale within Group Digital. This role will focus on developing and deploying machine learning models and neural networks, supporting MLOps practices, to enhance personalization and automation within our digital products. You will work closely with data engineers, product teams, and business stakeholders to build scalable data pipelines, CI/CD workflows, and ETL processes. The ideal candidate will have experience in retail, personalization, web technologies, and cutting-edge AI methods, including Large Language Models (LLMs), Generative AI, and Knowledge Graphs.
Key Responsibilities :
Machine Learning & AI Development
Develop and optimize predictive and prescriptive models to extract insights and enhance decision-making. Knowledgeable in supervised and unsupervised learning. Apply deep learning and neural network techniques for customer classification and profiling, customer segmentation, and personalization.
Utilize MLOps to efficiently deploy, monitor, and maintain ML models in production.
Implement and fine-tune Large Language Models (LLMs) and Generative AI solutions for automation and user engagement.
Explore and integrate knowledge graphs to enhance data relationships and improve AI-driven recommendations.
Data Engineering & Pipelines
Work with data engineers to design and develop robust data pipelines for large-scale ETL processing using SQL and cloud-based solutions (GCP preferred).
Write complex SQL queries for extracting, transforming, and loading (ETL) data efficiently. Implement CI/CD workflows to automate model training, deployment, and monitoring. Collaboration & Agile Development
Work in an Agile/DevOps environment, collaborating with cross-functional teams to drive data-driven innovation.
Promote a data-centric culture by educating teams on the strategic importance of AI and analytics.
Clearly communicate complex methodologies, results, and business insights to both technical and non-technical audiences.
Preferred Qualifications
Experience with Knowledge Graphs and their integration into AI/ML pipelines.
Hands-on experience in LLMs (e.g., GPT, BERT, LLaMA, Claude) and Generative AI technologies.
Background in Retail and Personalization Web Technologies.
Understanding of digital ecosystem and data-driven decision-making.
Proficiency in business intelligence (BI) tools and data visualization.
Education:
Bachelor's or Masterβs degree in Computer Science, Mathematics, Engineering, or related field.
Job Type: Contract
Pay: $45.00 - $51.00 per hour
Expected hours: 40 per week
Work Location: In person





