Net2Source Inc.

Data Scientist

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist in Philadelphia, PA, for 12+ months at a pay rate of "unknown." Requires 5+ years of experience in Data Science, proficiency in Python, SQL, and GCP, with a focus on retail and AI technologies.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
March 11, 2026
πŸ•’ - Duration
More than 6 months
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🏝️ - Location
On-site
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Philadelphia, PA
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🧠 - Skills detailed
#MLflow #DevOps #Deployment #Cloud #Monitoring #SQL Queries #Automation #Mathematics #Airflow #A/B Testing #Classification #Deep Learning #AI (Artificial Intelligence) #Neural Networks #TensorFlow #Unsupervised Learning #SQL (Structured Query Language) #Scala #Python #Customer Segmentation #Agile #Knowledge Graph #GCP (Google Cloud Platform) #"ETL (Extract #Transform #Load)" #Statistics #BERT #Data Science #Data Engineering #Data Pipeline #Model Deployment #PyTorch #BI (Business Intelligence) #ML (Machine Learning) #Visualization #Supervised Learning #Computer Science
Role description
Role: Data Scientist Location: Philadelphia, PA – Onsite Duration: 12+ Months 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, neural networks, support 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 Recommendation Engines, Large Language Models (LLMs), Generative AI, and Knowledge Graphs." Key Responsibilities: β€’ Machine Learning & AI Development β€’ 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, personalization. β€’ Utilize MLOps and GCP services to efficiently deploy, monitor, and maintain ML models in production. β€’ Implement and fine-tune Large Language Models (LLMs) and Generative AI solutions for automation and user engagement. β€’ Explore and integrate knowledge graphs to enhance data relationships and improve AI-driven recommendations. β€’ Data Engineering & Pipelines β€’ Work with data engineers to design and develop robust data pipelines for large-scale ETL processing using SQL and cloud-based solutions (GCP preferred). β€’ Write complex SQL queries for extracting, transforming, and loading (ETL) data efficiently. Implement CI/CD workflows to automate model training, deployment, and monitoring. β€’ Collaboration & Agile Development β€’ Work in an Agile/DevOps environment, collaborating with cross-functional teams to drive data-driven innovation. β€’ Promote a data-centric culture by educating teams on the strategic importance of AI and analytics. β€’ Clearly communicate complex methodologies, results, and business insights to both technical and non-technical audiences." Required Skills & Qualifications: β€’ 5+ years of experience in Data Science, Machine Learning, or related fields. β€’ Strong expertise in Python, SQL, and modern ML frameworks (TensorFlow, PyTorch, Scikit-Learn). β€’ Experience with MLOps tools (MLflow, Kubeflow, Airflow) for model deployment and monitoring. β€’ Proficiency in cloud platforms (GCP) and scalable data engineering. β€’ Experience implementing and testing recommendation engines. β€’ Strong understanding of probability theory, statistics, and experimental design (A/B Testing). β€’ Experience with collaborative software engineering practices (Agile, DevOps). β€’ Bachelor's or Master’s degree in Computer Science, Mathematics, Engineering, or related field. Preferred Qualifications: β€’ Background in Retail and Personalization Web Technologies. β€’ Experience with Knowledge Graphs and their integration into AI/ML pipelines. β€’ Hands-on experience in LLMs (e.g., GPT, BERT, LLaMA, Claude) and Generative AI technologies. β€’ Understanding of client’s digital ecosystem and data-driven decision-making. β€’ Proficiency in business intelligence (BI) tools and data visualization.