Data Scientist

Virtual Company; Clark (NJ); Hybrid; USD 69,000 - 75,000; Full time

Job summary

The Fountain Group is seeking a Data Scientist in Clark, NJ, for a 6-month contract with a possibility of extension. The role focuses on formulation, product development, and data-driven decisions in cosmetics/science domains.

Responsibilities include building predictive ML models, GenAI solutions, data exploration, and visualization. Requires a Master’s in a STEM field and 3+ years of experience with Python, SQL, and GenAI.

Qualifications

• Master's degree required in a STEM field.
• 3+ years of hands-on Data Science experience.
• Strong Python programming and statistical analysis.
• Experience with predictive ML and GenAI.
• SQL proficiency and data wrangling.
• Experience with data visualization tools (Power BI/Tableau).
• Git version control experience.
• Fluent English required.

Responsibilities

• Design, develop, and deploy predictive ML models (regression, classification, clustering, time-series).
• Develop GenAI solutions using RAG, prompt engineering, and vector databases.
• Choose ML/GenAI approaches based on performance and cost.
• Monitor production models for drift, bias, and cost.
• Explore and clean data from structured and unstructured sources.
• Build visualizations and dashboards to communicate insights.

Skills

Python programming

SQL

Data visualization

Git version control

Fluent English

Statistics

Education

Master's degree in Data Science, Statistics, Computer Science, Engineering, or related STEM field

Tools

Power BI

Tableau

Azure

AWS

GCP

Apache Spark

Databricks

Job description

The Fountain Group is currently seeking a Data Scientist for a prominent client of ours. This position is located at Clark, NJ.

Hybrid position - 3 days onsite / 2 days work from home

Pay: $50-54.43/hour W2 only

Duration: 6 months with possibility of extension

Job Title: Data Scientist - Formulation & Product Development

Job Description

Seeking a Data Scientist with 3+ years of experience developing predictive machine learning models and Generative AI solutions for real-world applications. The role focuses on leveraging data science, predictive analytics, and GenAI to support formulation, product development, and data-driven business decisions within the cosmetics and scientific domain.

Responsibilities

• Design, develop, validate, and deploy predictive ML models, including regression, classification, clustering, and time-series forecasting.
• Develop GenAI solutions using Retrieval-Augmented Generation (RAG), prompt engineering, vector databases, and AI frameworks.
• Select appropriate ML or GenAI approaches based on model performance, cost, and business value.
• Evaluate and monitor production models for performance, data drift, hallucinations, bias, and cost.
• Perform data exploration, cleaning, and analysis across structured and unstructured datasets.
• Build data visualizations and dashboards to communicate analytical results and support product development decisions.
• Identify and implement new data science and AI use cases.

Education

• Master's degree in Data Science, Statistics, Computer Science, Engineering, or a related STEM field required.

Required Skills

• 3+ years of hands-on Data Science experience.
• Demonstrated project experience in both Predictive Machine Learning and Generative AI.
• Strong Python programming and statistical analysis.
• Feature engineering, model validation, and ML experimentation.
• Regression, classification, clustering, and time-series forecasting.
• Prompt engineering and Retrieval-Augmented Generation (RAG) architectures.
• Vector databases and GenAI frameworks.
• Evaluation of GenAI-generated outputs.
• Advanced SQL.
• Data visualization using Power BI, Tableau, or equivalent tools.
• Git version control.
• Fluent English.

Preferred Skills

• Industry Experience: Cosmetics, pharmaceuticals, or other scientific domains, particularly R&D, formulation, ingredients, clinical studies, consumer studies, or regulated environments.
• GenAI fine-tuning and model adaptation.
• Agentic AI workflows and AI agents.
• MLOps / GenAIOps and production model monitoring.
• Cloud platforms: Azure, AWS, or GCP.
• Apache Spark and Databricks.
• French language proficiency.