Lead Data Scientist

Staffing Spot, Inc.; Woodbridge Township (NJ); On-site; USD 180,000 - 260,000; Full time

Job summary

Staffing Spot, Inc. is seeking a senior data scientist lead to drive end-to-end data science initiatives in a fast-paced environment.

You will translate business problems into predictive and prescriptive models, and mentor a team while collaborating with product and engineering to deploy scalable solutions. You will leverage Python, SQL, and modern ML frameworks, implement MLOps practices, ensure governance, and present strategic insights to leadership to inform data-driven decisions across the

Qualifications

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.
• 10 years of experience in data science, machine learning, or advanced analytics, depending on the organization.
• Strong proficiency in Python, SQL, and libraries such as pandas, scikit-learn, PyTorch, or TensorFlow.
• Expertise in supervised and unsupervised learning, feature engineering, model evaluation, and statistical methods.
• Experience deploying models using cloud platforms such as AWS, Azure, or GCP.
• Knowledge of ML pipelines, Docker, Kubernetes, CI/CD, and model monitoring.
• Strong communication, stakeholder management, and technical leadership skills.
• Strong hands-on experience building predictive machine learning models, recommender systems, ranking models, and prescriptive optimization models
• Strong proficiency in Python, SQL, MLOps, and modern AI/ML development frameworks (Scikit-learn, TensorFlow, PyTorch, Hugging Face, AWS Sagemaker, etc.)

Responsibilities

• Lead end-to-end data science projects, from problem definition to production deployment.
• Develop and optimize machine learning, deep learning, and statistical models.
• Design and implement Generative AI, LLM, and RAG-based solutions where applicable.
• Translate complex business problems into analytical and predictive solutions.
• Establish best practices for experimentation, model validation, explainability, and monitoring.
• Mentor data scientists and review technical deliverables.
• Partner with engineering, product, and business stakeholders.
• Drive MLOps practices, model governance, scalability, and responsible AI.
• Present analytical insights and recommendations to senior leadership.

Skills

Python

SQL

Pandas

Scikit-learn

PyTorch

TensorFlow

MLOps

Leadership

Cloud

Communication

Education

Bachelor's or Master's degree in CS/Stats/Math/Engineering

Tools

Docker

Kubernetes

CI/CD

ML pipelines

AWS Sagemaker

Hugging Face

Job description

Key Responsibilities

• Lead end-to-end data science projects, from problem definition to production deployment.
• Develop and optimize machine learning, deep learning, and statistical models.
• Design and implement Generative AI, LLM, and RAG-based solutions where applicable.
• Translate complex business problems into analytical and predictive solutions.
• Establish best practices for experimentation, model validation, explainability, and monitoring.
• Mentor data scientists and review technical deliverables.
• Partner with engineering, product, and business stakeholders.
• Drive MLOps practices, model governance, scalability, and responsible AI.
• Present analytical insights and recommendations to senior leadership.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.
• 10 years of experience in data science, machine learning, or advanced analytics, depending on the organization.
• Strong proficiency in Python, SQL, and libraries such as pandas, scikit-learn, PyTorch, or TensorFlow.
• Expertise in supervised and unsupervised learning, feature engineering, model evaluation, and statistical methods.
• Experience deploying models using cloud platforms such as AWS, Azure, or GCP.
• Knowledge of ML pipelines, Docker, Kubernetes, CI/CD, and model monitoring.
• Strong communication, stakeholder management, and technical leadership skills.
• Strong hands-on experience building predictive machine learning models, recommender systems, ranking models, and prescriptive optimization models
• Strong proficiency in Python, SQL, MLOps, and modern AI/ML development frameworks (Scikit-learn, TensorFlow, PyTorch, Hugging Face, AWS Sagemaker, etc.)

Skills: ml,machine learning,data science,aws,leadership,sql,data,artificial intelligence,data models,python