Lead Data Scientist

  • Atlanta, GA
  • Posted 2 hours ago | Updated 2 hours ago

Overview

Remote
On Site
Hybrid
$70 - $100
Accepts corp to corp applications
Contract - W2
Contract - Independent
Able to Provide Sponsorship

Skills

Algorithms
Analytical Skill
Artificial Intelligence
Attention To Detail
Cloud Computing
Cloud Security
Cloud Storage
Collaboration
Communication
Computer Science
Conflict Resolution
Continuous Delivery
Continuous Integration
Data Analysis
Data Flow
Data Visualization
Decision-making
Evaluation
Good Clinical Practice
Google Cloud
Google Cloud Platform
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Management
Mathematics
Optimization
Problem Solving
PyTorch
EDA
Python
Rapid Prototyping
Real-time
SQL
Statistics
TensorFlow
Training
Vertex
Workflow
scikit-learn

Job Details

We are looking for a skilled Data Scientist with hands-on experience on Google Cloud Platform (Google Cloud Platform) and Vertex AI to design, develop, and deploy scalable machine learning solutions. The ideal candidate will have experience in end-to-end ML workflows, model training, deployment, and monitoring using Google Cloud Platform services.

Key Responsibilities

  • Design, implement, and maintain ML models on Vertex AI, including training pipelines, model versioning, and deployment.

  • Collaborate with data engineers to prepare, clean, and validate large datasets from multiple sources.

  • Conduct exploratory data analysis (EDA) and feature engineering to improve model performance.

  • Build and optimize ML pipelines using Vertex AI Pipelines and integrate with other Google Cloud Platform services (BigQuery, Cloud Storage, Dataflow, Pub/Sub).

  • Develop and deploy ML models in production environments, monitor model performance, and troubleshoot issues.

  • Apply advanced statistical methods and machine learning algorithms to solve complex business problems.

  • Stay up-to-date with the latest trends and best practices in cloud ML platforms and AI technologies.

  • Collaborate with cross-functional teams to translate business requirements into ML solutions.

Required Skills & Qualifications

  • Educational Qualification: Bachelor s or Master s degree in Computer Science, Statistics, Mathematics, or a related field.

  • Cloud Expertise: Hands-on experience with Google Cloud Platform services such as BigQuery, Cloud Storage, Dataflow, Pub/Sub, AI Platform, and Vertex AI.

  • ML Frameworks: Proficiency in TensorFlow, PyTorch, or Scikit-learn.

  • Programming: Strong coding skills in Python; familiarity with SQL.

  • Data Handling: Experience in handling structured and unstructured datasets, feature engineering, and data preprocessing.

  • Model Deployment: Knowledge of deploying ML models using Vertex AI endpoints, containerized deployment, and CI/CD pipelines.

  • Monitoring & Evaluation: Track model performance, implement model retraining strategies, and apply ML interpretability techniques.

  • Analytical Skills: Strong problem-solving, statistical analysis, and data visualization skills.

Preferred Qualifications

  • Certifications: Google Cloud Platform Professional Data Engineer, TensorFlow Developer Certificate.

  • Experience with MLOps, Kubeflow, or Airflow.

  • Familiarity with AutoML on Vertex AI for rapid prototyping.

  • Exposure to real-time prediction pipelines and event-driven ML architectures.

  • Strong understanding of cloud security, cost optimization, and governance.

Soft Skills

  • Excellent communication and collaboration skills.

  • Ability to work independently and manage multiple projects simultaneously.

  • Strong attention to detail and data-driven decision-making mindset.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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