Amazon Web Services (AWS), Artificial Intelligence (AI), Business Intelligence, Cloud Computing, Communication Skills, Computer Science, Data Science, Data Sets, Data Visualization Tools, Deep Learning, Interpersonal Skills, Machine Learning, Microsoft Windows Azure, Model Validation, Operations Management, Performance Metrics, Performance Modeling, Power BI, Predictive Modeling, Problem Solving Skills, Project/Program Management, Reporting Dashboards, Science Library, Statistics, Technical Leadership
Role : Senior Data Scientist
Location : Holtsville NY (Hybrid)
Rate : $72/hr.
Job Description:
• Design, build, and validate robust predictive models and machine learning solutions
to address specific business problems.
• Process, cleanse, and transform large, complex datasets from various sources to
create high-quality features for modeling.
• Create comprehensive documentation for all models, code, and data pipelines to
ensure transparency and facilitate a smooth handover at the end of the contract.
• Develop and present findings, model performance metrics, and project outcomes to
technical leads and project managers, often through dashboards in tools like Power
BI.
Minimum Education
• Bachelor's or advanced degree (Master's/Ph.D.) in
computer science, data science, artificial intelligence,
or a related field.
Minimum Work Experience (years)
5+ years - strong background in statistics, machine learning,
deep learning and programming
Key Skills and Competencies
Technical Skills:
• Strong foundation in machine learning, deep learning,
and AI frameworks
• Familiarity with tools and platforms such as
TensorFlow, PyTorch, Databricks, Google BigQuery, and
cloud-based AI services (AWS, Google Cloud, Azure).
• Familiarity with data visualization tools like Power BI or
similar.
• Expert-level proficiency in Python and its core data
science libraries (e.g., pandas, NumPy, scikit-learn).
Strong SQL for complex data extraction is mandatory.
• Understanding of MLOps practices and tools (e.g.,
MLflow, Kubeflow) to ensure operational efficiency in
AI pipelines.
• Strong knowledge of data preprocessing, feature
engineering, and model evaluation techniques.
• Strong interpersonal and communication skills to
effectively translate technical concepts for non
technical stakeholders.
Licenses, Certifications or Special
Qualifications
• Preferred: Certifications such as Google Cloud
Professional Machine Learning Engineer, AWS Certified
Machine Learning – Specialty, or Microsoft Certified:
Azure AI Engineer Associate.