استخدام Senior Data Scientist

Programming Skills:
Proficiency in Python (highly preferred) or R.
Strong command over programming paradigms required for data manipulation and modeling.

Database & Data Management:
Solid understanding of SQL and experience with both relational and non-relational databases.
Proven ability to handle large-scale data environments.

Machine Learning & Statistical Modeling:
Strong background in machine learning principles, including supervised and unsupervised learning techniques.

Communication & Collaboration:
Ability to clearly communicate complex technical concepts to both technical and non-technical stakeholders.

Specific Skills
Time Series Analysis:
Experience with time series forecasting and analysis techniques, including trend analysis, seasonality, and anomaly detection.

Artificial Intelligence & Machine Learning:
Expertise in AI-driven methods and algorithms such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
Experience in applying advanced deep learning techniques.

CI/CD for Data Science:
Familiarity with Continuous Integration and Continuous Deployment (CI/CD) practices for streamlining model deployment and
ensuring robust, reproducible pipelines.

PyTorch Proficiency:
Hands-on experience with PyTorch for building, training, and fine-tuning deep learning models.
Understanding of model optimization and GPU-based computations.

Data Engineering & Feature Engineering:
Skills in collecting, cleaning, and structuring data.
Experience in feature engineering to enhance model performance.

Model Development & Monitoring:
Ability to design, develop, deploy, and monitor predictive models in production environments.
Responsibilities

Project Management & Strategy:
Identify, formulate, and manage data-driven projects aligned with business 

Cross-Functional Collaboration:
Work closely with product managers, software engineers, and business analysts to integrate data science solutions.


Continuous Improvement & Innovation:
Stay current with the latest advancements in data science, AI, and related technologies.


Preferred Qualifications
Advanced Academic Credentials:
A Master’s or Ph.D. in a relevant field is advantageous.

Domain-Specific Experience:
Experience in finance or other industry-specific applications is considered a plus.
Additional knowledge in image processing and Natural Language Processing (NLP) can be beneficial.

Big Data & Stream Processing:
Familiarity with big data tools and platforms such as Spark, Hive, Kafka, etc., is desirable.

Team Leadership:
Lead initiatives that drive the adoption of best practices within the team