Data Scientist
Backend Developer
Artificial Intelligence
Cloud Operations
Cloud Platforms
Data
Data Analysis
Data Analytics
Data Architecture
Data Integration
Data Pipeline
Data Platform
Data Processing
Data Science
Data Scientist
Databases
Databricks Mlflow
ETL
Generative AI
Google Cloud
Informatica
Large Language Models
Machine Learning
Machine Learning Engineer
Ml Pipelines
MLOps
Neural Networks
Job Description
Experis is seeking a Data Scientist to support a client team within the Digital Transformation Department in Philadelphia, PA (onsite). The position centers on developing advanced machine learning and neural network solutions, delivering personalization and automation outcomes, and applying Generative AI and LLM capabilities within scalable pipelines and MLOps practices.
Role Focus
- Develop and implement advanced machine learning models and neural networks for personalization and automation initiatives.
- Apply deep learning methods for customer segmentation, profiling, and classification to improve user engagement.
- Build and fine-tune Large Language Models (LLMs) and Generative AI solutions aimed at process automation and enhanced user experience.
- Use knowledge graphs and other AI techniques to enrich data relationships and optimize recommendation systems.
Responsibilities
- Lead the development and deployment of advanced machine learning models and neural networks.
- Work with data engineers, product teams, and business partners to design scalable data pipelines, CI/CD workflows, and ETL processes.
- Apply deep learning approaches for customer segmentation, profiling, and classification to support engagement goals.
- Implement and fine-tune LLMs and Generative AI solutions for automation and user experience improvements.
- Leverage knowledge graphs and additional AI techniques to improve data relationships and recommendation system performance.
Requirements
- 7-10 years of proven experience in Data Science, Machine Learning, or related fields.
- Strong proficiency in Python and SQL, with experience using modern ML frameworks such as TensorFlow, PyTorch, and Scikit-Learn.
- Hands-on experience with MLOps tools including MLflow, Kubeflow, and Airflow for deploying and monitoring models.
- Experience with cloud platforms such as GCP and AWS, including scalable data engineering.
- Knowledge of knowledge graphs (Neo4j preferred), and experience with LLMs and Generative AI technologies such as GPT, BERT, and LLaMA.
Tools and Technologies
- Python, SQL
- TensorFlow, PyTorch, Scikit-Learn
- MLflow, Kubeflow, Airflow
- GCP, AWS
- Neo4j
- GPT, BERT, LLaMA
Location
Philadelphia, PA (Onsite)
Benefits
- Work on cutting-edge AI and machine learning projects in a dynamic environment.
- Collaborate with innovative teams and industry leaders in digital transformation.
- Develop skills through exposure to cloud platforms, MLOps, and advanced AI techniques.
- Join a forward-thinking organization focused on technological advancement.
- Contribute to impactful projects related to digital personalization and automation.