Added 1 week ago
Data Scientist
LocationAbu-Dhabi, Abu Dhabi, Middle East Staffing Adecco
Job typeSpecialist
Date2025-01-07
CategoryIT and Telecommunications
Data Scientist
Key Responsibilities
- Data cleaning and processing: Perform data cleaning, transformation, and integration to prepare structured data for analysis and modelling
- Data pipeline maintenance: Maintain and update data pipelines and infrastructure components to support model deployment and data flow.
- Model and data reliability: Conduct reliability checks on data and model outputs to ensure consistency and accuracy across all projects.
- Technical growth: Take ownership of personal development by working on complex projects and actively seeking feedback from senior team members.
- Data analysis execution: Analyse structured and unstructured data sets to identify patterns and generate actionable insights using analytical techniques.
- Predictive model development: Develop predictive models using standard algorithms and validate model performance for specific business scenarios.
- Hypothesis testing execution: Design and conduct hypothesis testing using A/B testing methods, ensuring accurate interpretation of results.
- Data visualization creation: Create clear and informative data visualizations using industry-standard tools to communicate key findings.
- Feature engineering implementation: Implement feature engineering techniques to optimize model performance and ensure predictive reliability.
- Model evaluation and improvement: Evaluate model performance and refine the model iteratively to improve predictive accuracy.
- Project collaboration: Collaborate with team members and other departments to ensure smooth execution of data-centric projects.
- Comprehensive documentation: Maintain meticulous documentation of best practices, methodologies, data lineage, model development, and analytical findings to ensure transparency and reproducibility
- Continuous learning: Remain at the vanguard of data science by keeping abreast of emerging technologies, methodologies, and industry best practices
Desired Experience and Qualifications
- Bachelor's degree or above in computer science, computer engineering, information technology, statistics, mathematics, business analytics or a related quantitative field
- 3+ years of experience in data science or a related analytical field.
- Experience applying software engineering methodologies and best practices including coding standards, code reviews, build processes, testing, and security.
- Prior experience in developing AI solutions on public cloud services is an advantage.
- Technical Expertise:
- Programming languages: Python (pandas, NumPy, scikit-learn) R, Java, Scala
- Statistical analysis & machine learning: Regression, classification, clustering, neural networks, time-series forecasting, deep learning etc.
- Generative AI: Experience in building and fine-tuning transformer models for text, image, video, or audio using PyTorch or TensorFlow.
- GPUs: Experience in using multi-GPUs for pretraining models, optimizing performance, and accelerating the development of generative AI solutions.
- Data management & databases: Oracle, SAP, SQL, NoSQL (e.g., MongoDB, Cassandra), Data Warehousing
- Big data technologies: Apache Hadoop, Spark, Kafka, etc.
- Cloud platforms: Microsoft Fabric, Azure (Synapse Analytics, Databricks, Machine Learning, AI Search, Functions, etc.), AWS (S3, Redshift, SageMaker, etc.), Google Cloud Platform (BigQuery, Dataflow, etc.),
- Data visualization: Matplotlib, Seaborn, Tableau, Power BI
- DevOps & MLOps: CI/CD principles, Docker, MLFlow, Kubernetes
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