Data Scientist

Capgemini; Philadelphia (Philadelphia County); On-site; USD 51,000 - 80,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

Retirement plan

Job summary

Tundra Technical Solutions seeks a seasoned Data Scientist in Philadelphia, PA to lead scalable ML models and MLOps practices. You will collaborate with data engineers, product teams, and business partners to craft data pipelines, CI/CD workflows, and ETL processes using SQL and cloud solutions, with a focus on personalization and automation.

The role emphasizes deep learning, neural networks, and knowledge graphs, leveraging LLMs and Generative AI to improve customer experiences in

Qualifications

• 10+ years in Data Science, ML or related fields.
• Strong Python, SQL, and ML framework experience (TF, PyTorch, Scikit-Learn).
• Experience with MLOps tools for deployment and monitoring.
• Proficiency in GCP and AWS cloud environments.
• Knowledge of probability, statistics, and experimental design.
• Experience with Knowledge Graphs and Neo4j integration.
• Hands-on experience with LLMs and Generative AI.
• Retail/personalization tech experience is a plus.

Responsibilities

• Develop and optimize predictive and prescriptive models.
• Write complex SQL for ETL processes.
• Implement ML models and MLOps workflows in production.
• Collaborate with data engineers and product teams.
• Design and deploy CI/CD for model training and deployment.
• Utilize LLMs and Generative AI for automation and engagement.
• Leverage knowledge graphs to enhance recommendations.

Skills

Python

SQL

TensorFlow

PyTorch

Scikit-Learn

MLOps

GCP

AWS

Data Visualization

Agile/DevOps

Education

Bachelor's degree in CS/Math/Engineering

Tools

MLflow

Kubeflow

Airflow

Neo4j

Job description

Philadelphia, PA, United States (On-site)

Contract (10 months 17 days)

Published 3 days ago

On hold

LLMs

SQL

tensorflow

DevOps & CI/CD

Python

MLOps tools

We seek a highly skilled Data Scientist located in Philadelphia, PA to lead the implementation of algorithmic decision‑making at scale within Group Digital.

This role will center on crafting and implementing machine learning models, neural networks, and supporting MLOps practices to enhance personalization and automation within our digital products.

The chance to work on innovative AI methods and technologies makes this role exceptionally exceptional and thrilling

You will collaborate with data engineers, product teams, and business partners to develop scalable data pipelines, CI/CD workflows, and ETL processes.

The preferred candidate will have expertise in retail, personalization web technologies, GCP, and groundbreaking AI techniques, such as Large Language Models (LLMs), Generative AI, and Knowledge Graphs, preferably experience with Neo4j.

Your Role:

We develop and optimize predictive and prescriptive models to extract insights and improve decision‑making.

Clearly communicate complex methodologies, results, and business insights to both technical and non‑technical audiences.

Apply deep learning and neural network techniques for customer classification, profiling, customer segmentation, and personalization!

Apply 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.

We explore and integrate knowledge graphs to enhance data relationships and improve recommendations.

We work with data engineers to craft 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.

Work in an Agile/DevOps environment, collaborating with cross‑functional teams to drive data‑driven innovation.

We promote a data‑centric culture by educating teams on the strategic importance of AI and analytics.

Your skills and experience:

7-10 years of proven 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 Google Cloud Platform (GCP), AWS, and scalable data engineering.

Strong understanding of probability theory, statistics, and experimental design (A/B Testing).

Experience with collaborative software engineering practices (Agile, DevOps).

Experience with Knowledge Graphs (including the Neo4j tool) 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.

Proficiency in business intelligence (BI) tools and data visualization.

Bachelor's degree or equivalent experience in Computer Science, Mathematics, Engineering, or related field.

The pay range that the employer in good faith reasonably expects to pay for this position is $36.98/hour - $57.79/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.

Tundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.