Lead Data Scientist

Staffing Spot, Inc.

Columbus (OH)

Presencial

USD 140.000 - 200.000

Jornada completa

hace 11 horas
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Descripción de la vacante

Staffing Spot, Inc. is seeking a seasoned data science leader to drive end-to-end projects from problem definition to production deployment.

You will develop and optimize ML, DL, and statistical models, and design Generative AI/Large Language Model solutions where applicable. You will translate business problems into predictive solutions, establish best practices, mentor staff, and collaborate with engineering, product, and business teams to scale MLOps and governance.

Formación

  • 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.)

Responsabilidades

  • 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.

Conocimientos

Leadership
Communication
Mentoring
Problem solving

Educación

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

Herramientas

Python
SQL
pandas
scikit-learn
PyTorch
TensorFlow
Hugging Face
AWS SageMaker
Docker
Kubernetes
CI/CD
Model monitoring

Descripción del empleo

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

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