
AI and ML Strategist
19 hours ago
We are seeking an experienced leader to spearhead our Artificial Intelligence (AI) and Machine Learning (ML) initiatives.
Key Responsibilities:
- Strategy and Vision: Define and drive the company's AI/ML strategy in alignment with overall business objectives.
- Tech Lead: Lead a team of AI/ML engineers and data scientists, fostering innovation and excellence.
- Cross-Functional Collaboration: Collaborate with various teams to integrate AI/ML capabilities into existing platforms.
Technical Expertise:
- Model Development: Oversee the design, development, and deployment of AI/ML models and technologies to solve complex problems.
- Solution Scalability: Ensure the scalability, reliability, and performance of AI/ML solutions.
- Industry Knowledge: Stay abreast of the latest advancements in AI/ML technologies and evaluate their potential impact on the platform.
Project Management:
- Multi-Project Handling: Manage multiple AI/ML projects simultaneously, ensuring timely delivery within scope and budget.
- Progress Tracking: Develop and maintain project plans, track progress, and report on project status to senior management.
Stakeholder Engagement:
- Internal Partnerships: Work closely with internal stakeholders to understand their needs and provide AI/ML solutions.
- External Relations: Engage with external stakeholders to demonstrate the value of AI/ML capabilities.
Compliance and Risk Management:
- Regulatory Compliance: Ensure that all AI/ML initiatives comply with relevant regulations and industry standards.
- Risk Identification: Identify and mitigate risks associated with AI/ML implementations.
Qualification Experience:
A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field. A Ph.D. is a plus.
10 to 15 years of experience in AI/ML technologies, with a significant portion spent in the banking or financial services industry.
Required Skills:
- Leadership Experience: Proven leadership experience, including leading technical teams and managing complex projects.
- Technical Expertise: Strong expertise in machine learning algorithms, data analysis, natural language processing, and generative AI technologies.
- Familiarity with Tools: Hands-on experience with AI/ML frameworks and tools such as TensorFlow, PyTorch, scikit-learn, Keras, and others.
- Programming Languages: Proficient in programming languages such as Python, R, and SQL.
- Data Preprocessing: Experience with data preprocessing, feature engineering, and model evaluation techniques.
- MLOps Practices: Familiarity with MLOps practices and tools for model deployment, monitoring, and maintenance.
- Cloud Computing: Knowledge of cloud computing platforms and services (e.g., AWS, Azure, Google Cloud) for AI/ML workloads.
- Ethical Principles: Understanding of ethical AI principles and data privacy regulations.
- Problem-Solving Skills: Excellent problem-solving skills and the ability to think strategically and analytically.
- Communication Skills: Strong communication and interpersonal skills, with the ability to effectively convey technical concepts to non-technical stakeholders.
Preferred Skills:
- Low-Code/No-Code Platforms: Experience with Low-Code/No-Code platforms.
- Banking Regulations: Knowledge of banking regulations and compliance requirements.
- Big Data Technologies: Experience with big data technologies (e.g., Hadoop, Spark) and data visualization tools (e.g., Tableau, Power BI).
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