Data Scientist with Gen AI
Description:
Hiring: W2 Candidates Only
Location: USA
Visa: Open to any visa type with valid work authorization in the USA
Experience Required: 6 to 12 years
Level: Mid to Lead positions
Key Responsibilities
Data Analysis & Modeling: Analyze large datasets to identify patterns and trends, developing predictive models using ML algorithms like regression, classification, and clustering.
AI Model Development: Design, train, and deploy AI models, including natural language processing (NLP) systems, computer vision applications, and time series forecasting.
Data Integration & Pipeline Management: Integrate data from various sources, ensuring data quality and consistency. Utilize tools like Apache Airflow for workflow automation and manage data pipelines effectively.
Cloud & MLOps: Deploy AI models on cloud platforms such as AWS, Azure, or GCP. Implement MLOps practices to streamline model deployment, monitoring, and maintenance.
Visualization & Reporting: Create interactive dashboards and visualizations using tools like Power BI or Tableau to present insights to stakeholders.
Collaboration & Communication: Work closely with cross-functional teams, including data engineers, product managers, and business analysts, to align AI solutions with business objectives.
️ Essential Skills
Programming Languages: Proficiency in Python and R; experience with SQL and Java is a plus.
AI/ML Frameworks: Familiarity with TensorFlow, PyTorch, Keras, and scikit-learn.
Data Processing & Visualization: Experience with Pandas, NumPy, Matplotlib, and data visualization tools.
Cloud Platforms: Knowledge of cloud services like AWS, Azure, or GCP for model deployment.
Soft Skills: Strong problem-solving abilities, effective communication, and teamwork.
Experience Requirements
Experience: 6-12 years in data science or AI roles, with a proven track record of deploying AI solutions in production environments.
Certifications: Certifications like Azure AI Engineer Associate or TensorFlow Developer can be advantageous.