Data Science and AI Manager
Job Location:
Monthly Salary:
Posted on:
8 hours ago
Posted on:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Description
Responsibilities
Qualifications
Responsibilities
- Technical Leadership:
- Lead mentor a team of data scientists fostering a collaborative and innovative environment.
- Provide technical guidance and oversight throughout the solution development lifecycle.
- Drive best practices in MLOps model development testing and deployment.
- Stay abreast of the latest advancements in AI/ML and recommend their application to relevant business challenges.
- Hands-on AI ML Development:
- Design build and deploy end-to-end AI/ML models and systems that address critical after-sales service needs.
- Develop robust scalable and production-ready code for AI ML applications.
- Perform data exploration feature engineering model training evaluation and optimization.
- Integrate AI ML solutions with existing enterprise systems and data pipelines.
- Strategy & Collaboration:
- Collaborate closely with product managers data scientists business stakeholders and IT teams to understand requirements define project scope and deliver impactful AI ML solutions.
- Translate complex business problems into well-defined AI/ML technical requirements and architectural designs.
- Problem Solving:
- Identify opportunities to leverage AI ML to improve efficiency reduce costs and enhance customer satisfaction in after-sales service.
- Debug and troubleshoot complex AI ML systems and data issues.
Qualifications
- 5 years of professional experience in Artificial Intelligence Machine Learning or Data Science roles.
- 2 years of experience leading or mentoring a small team of engineers or data scientists.
- Strong hands-on programming proficiency in Python (including libraries like TensorFlow PyTorch scikit-learn pandas numpy).
- Demonstrated experience in designing building and deploying machine learning models into production environments.
- Solid understanding of machine learning algorithms (e.g. supervised unsupervised reinforcement learning deep learning) and their practical applications.
- Experience with Natural Language Processing (NLP)/LLM/Gen AI techniques and tools.
- Experience with cloud platforms (e.g. GCP AWS Azure) for AI/ML development and deployment.
- Experience with MLOps practices and tools (e.g. MLflow Kubeflow Docker Kubernetes).
- Knowledge of causal inference reinforcement learning or optimization techniques.
- Excellent problem-solving skills and the ability to work independently and as part of a team.
- Strong communication and interpersonal skills with the ability to explain complex technical concepts to non-technical stakeholders.
Required Experience:
Manager
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