Junior Data Scientist
Cultiv -
Cairo, EgyptPosted 1 year ago354Applicants for1 open position
- 68Viewed
- 0In Consideration
- 9Not Selected
Job Details
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Job Description
As a Junior Data Scientist, you will contribute to the development and implementation of data-driven solutions. Working closely with senior data scientists and other cross-functional teams, you will apply statistical analysis and machine/deep learning techniques to extract valuable insights from large datasets. This role presents a good opportunity for professional growth in a dynamic and collaborative environment.
Responsibilities:
- Clean, process, and analyze large datasets to identify patterns, association and trends.
- Work with different data types including (text, images, speech, and categorical data).
- Develop and implement machine-learning models for predictive and prescriptive analytics.
- Contribute to the design and optimization of algorithms to solve specific business problems.
- Create clear and insightful visualizations to communicate findings to both technical and non-technical stakeholders.
- Work closely with cross-functional teams, including business experts and software developers (Backend and frontend), to integrate data science solutions into existing systems.
- Document data sources, methodologies, and results to ensure transparency and reproducibility.
Job Requirements
Qualifications:
- Bachelor's or Master's degree in a relevant field (e.g., Computer Science, Information Technology, Statistics, Mathematics, or any related discipline).
- Solid understanding of statistical concepts and machine/deep learning algorithms.
- Proficiency in programming languages such as Python.
- Experience with data manipulation libraries (e.g., Pandas, NumPy) and machine learning frameworks (e.g., scikit-learn, PyTorch, or TensorFlow).
- Previous exposure to natural language processing (NLP) and deep learning.
- Strong analytical and problem-solving skills.
- Excellent communication skills, with the ability to convey complex concepts to both technical and nontechnical audiences.
- Knowledge of cloud platforms (e.g., AWS, Azure, or Google Cloud).
- Understanding of database systems and SQL.
- Familiarity with data visualization tools and techniques.
