Data Science Manager

2 weeks ago

جدة, Saudi Arabia Salla Full time

**Responsibilities**:

- Team Leadership: Manage and mentor a diverse team of data scientists, machine learning engineers, MLOps professionals, and business analysts. Foster a collaborative and innovative environment.
- Project Management: Lead the conception, planning, and execution of data science projects. Align these projects with organizational goals and ensure timely delivery.
- Data Analysis and Model Building: Oversee the analysis of raw data, including quality assessment, cleansing, preprocessing, and structuring for downstream processing. Supervise the development and implementation of machine learning models across various domains.
- Research and Development: Conduct R&D activities in data science and machine learning practices. Utilize deep learning techniques to solve complex problems in areas such as recommendation engines, chatbots, and natural language processing (NLP).
- Model Deployment: Collaborate with engineering and product teams to ensure seamless integration of AI models into production. Provide technical guidance and support during deployment.
- Innovation and Solution Design: Design and develop scalable machine learning models, ensuring accuracy and effectiveness. Create new service offerings and solutions in e-commerce and other fields.
- Cross-Functional Collaboration: Work closely with data engineers, quality assurance officers, business analysts, and software developers to translate ideas and prototypes into robust solutions.
- Continuous Learning: Stay abreast of the latest trends and advancements in data science, machine learning, and large language models (LLMs) to drive innovation within the team.
- Stakeholder Communication: Communicate complex data insights and model outcomes to stakeholders, ensuring clarity and alignment with business objectives.

**Requirements**:

- Experience: Minimum of 7 years in a leadership role managing data science projects and teams. At least 12 years of experience in data science, quantitative analytics, and data modeling.
- Educational Background: Post-graduate degree in a quantitative field such as Statistics, Mathematics, Computer Science, or Engineering.
- Technical Expertise: Deep understanding of predictive modeling, machine learning, clustering, and classification techniques. Proven experience with deep learning algorithms and LLMs.
- Programming Skills: Proficiency in Python and its libraries (TensorFlow, Keras, Pandas, Scikit-learn). Familiarity with other programming languages (Shell Scripts, C++,.Net, Java, Matlab, R) is an advantage.
- Big Data and Databases: Familiarity with database technology, query languages,, big data frameworks (Elasticsearch, Cassandra, Hadoop, Spark), cloud environments (AWS, Snowflake). Knowledge of data management and visualization techniques.
- Analytical Skills: Strong problem-solving abilities with a solid grasp of algorithms and object-oriented programming.
- Project Management: Demonstrated organizational, leadership, and project management skills. Ability to prioritize and manage multiple projects simultaneously.
- Communication Skills: Excellent communication and presentation skills, with the ability to convey complex concepts to both technical and non-technical stakeholders.
- Business Acumen: A strong business mindset with the ability to align data products and AI models with organizational goals.

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