Senior Data Scientist — AI, MLOps & Personalization

SGS Consulting; Philadelphia (Philadelphia County); Remote; USD 140,000 - 180,000; Full time

Job summary

SGS Consulting seeks an experienced data scientist to develop and optimize predictive and prescriptive models that improve decision-making across retail and personalization domains. You will implement supervised and unsupervised learning and deliver production‑grade ML solutions.

You will apply deep learning, use MLOps for deployment and monitoring, and explore knowledge graphs and LLMs to boost recommendations and customer engagement. Collaboration and rigorous experimental design are essential.

Qualifications

• 5+ years of experience in Data Science, ML, or related fields.
• Strong Python, SQL, and ML framework skills.
• Experience with MLOps tools for deployment and monitoring.
• Proficiency in cloud platforms and scalable data engineering.
• Solid understanding of probability, statistics, and experimental design.
• Experience with Agile/DevOps practices.
• Bachelor's or Master’s degree in CS/Math/Engineering or related field.

Responsibilities

• 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 deploy, monitor, and maintain ML models in production.
• Implement and fine‑tune LLMs and Generative AI solutions for automation and user engagement.
• Explore and integrate knowledge graphs to enhance data relationships and recommendations.

Skills

Python

SQL

ML frameworks

MLOps

Cloud platforms

A/B testing

Agile/DevOps

Knowledge graphs

Education

Bachelor's or Master’s degree

Tools

TensorFlow

PyTorch

Scikit-Learn

MLflow

Kubeflow

Airflow

AWS

GCP

Job description

SGS Consulting seeks an experienced data scientist to develop and optimize predictive and prescriptive models that improve decision-making across retail and personalization domains. You will implement supervised and unsupervised learning and deliver production‑grade ML solutions.

You will apply deep learning, use MLOps for deployment and monitoring, and explore knowledge graphs and LLMs to boost recommendations and customer engagement. Collaboration and rigorous experimental design are essential.