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Job Title: Data Scientist
Key Responsibilities
Key Responsibilities
- Data Cleaning and Preprocessing: Perform data cleaning, transformation, and preprocessing to ensure high-quality datasets for analysis and modelling.
- Machine Learning Algorithms: Develop and implement machine learning models using algorithms such as Random Forest, XGBoost, and others to solve complex problems.
- Forecasting: Utilize statistical and machine learning techniques for time series forecasting and predictive analytics.
- Python Programming: Leverage Python packages such as scikit-learn, pandas, and others for data analysis, modelling, and visualization.
- Artificial Intelligence: Apply AI techniques in computer vision, natural language processing (NLP), and generative AI using models like transformers and BERT. Incorporate prompt engineering and retrieval-augmented generation (RAG) applications.
- Cloud Computing: Deploy and manage machine learning and AI models on cloud platforms such as Azure or AWS, utilizing cognitive services.
- Database Management: Work with SQL and NoSQL databases, including Amazon Redshift and vector stores/DBs, to store, retrieve, and manage data efficiently.
- Model Development and Deployment: Develop, test, and deploy machine learning and AI models, ensuring scalability and performance. Implement REST APIs using SOAP, Flask, Swagger, and Postman.
- Data Visualization: Create insightful visualizations and dashboards using tools like Power BI or Tableau.
- MLOps: Design and implement MLOps pipelines for continuous integration, continuous deployment (CI/CD), and monitoring of machine learning models. Ensure seamless deployment of models on cloud platforms and maintain robust pipelines for model updates and management.
- Research and Innovation: Stay updated with the latest research and advancements in data science, AI, and machine learning to continuously improve solutions.
- Certifications: Maintain relevant certifications to demonstrate expertise and commitment to professional development.
- Bachelor's or master’s degree in data science, Computer Science, Statistics, or a related field.
- Proven experience in data cleaning, preprocessing, and analysis.
- Strong proficiency in machine learning algorithms, including Random Forest and XGBoost.
- Experience with time series forecasting and predictive analytics.
- Proficient in Python and relevant libraries (scikit-learn, pandas, etc.).
- Knowledge of AI techniques in computer vision, NLP, and generative AI (transformers, BERT). Experience with prompt engineering and RAG applications.
- Experience with cloud platforms (Azure, AWS) and cognitive services.
- Familiarity with SQL and NoSQL databases, including Amazon Redshift and vector stores/DBs.
- Demonstrated ability to develop and deploy ML and AI models. Experience with REST APIs using SOAP, Flask, Swagger, and Postman.
- Proficiency in data visualization tools like Power BI or Tableau.
- Experience with MLOps practices, including CI/CD pipelines and model monitoring.
- Strong research skills and ability to stay current with industry trends.
- Relevant certifications in data science, machine learning, or cloud computing.
Key Skills
Ranked by relevance
machine learning
ai
cloud
computer vision
power bi
python
pandas
nosql
flask
mlops
cicd
sql
aws
natural language processing
continuous integration
continuous deployment
data visualization
research skills
data analysis
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- Posted
- Feb 14, 2025
- Type
- Contract
- Level
- Not Applicable
- Location
- Dubai
- Company
- Dicetek LLC
Industries
IT Services
IT Consulting
Categories
Engineering
Information Technology
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3 roles aligned with this opportunity
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