Position Overview
The Director will lead a team of data scientists, machine learning engineers, and AI researchers. This hands-on role involves driving strategy, developing advanced AI models, and ensuring the successful deployment of AI solutions across various business functions.
What You’ll Do For Us
- Business Collaboration: Work closely with cross-functional teams to understand business requirements, including Finance, Marketing, and Supply Chain, and translate them into AI/ML solutions.
- Model Development: Develop, implement, and optimize ML and AI algorithms to predict outcomes and derive insights from large structured and unstructured datasets.
- End-to-End Solutions: Oversee the complete lifecycle of AI/ML projects, from ideation to deployment and monitoring.
- Data Insights: Visualize and interpret data, creating actionable reports and insights.
- Scalability: Partner with ML Ops and other cross-functional teams to scale and operationalize ML and AI use-cases.
- Knowledge Sharing: Build and maintain a robust library of reusable data science solutions, templates, and code.
- Automation: Utilize CI/CD principles to automate deployments and improve repeatability.
- Stakeholder Communication: Clearly communicate complex analytical work to both technical and non-technical stakeholders, including executive management.
- Mentorship: Mentor and guide junior and aspiring data scientists within the organization.
- Innovation: Stay current with industry trends and advancements in data science, machine learning, and generative AI.
Qualifications And Requirements
- Education: Advanced degree (Ph.D. preferred) in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, or a related field.
- Experience: At least 10+ years in data science, machine learning, and AI, with a proven track record of delivering successful projects.
- Technical Skills: Expertise in programming languages (Python, R, SQL) and machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Big Data: Experience with big data technologies (Hadoop, Spark, PySpark) and cloud platforms (AWS, Azure, GCP).
- Generative AI: Familiarity with generative AI techniques such as GANs, autoencoders, and transformers.
- Soft Skills: Strong problem-solving skills, attention to detail, and the ability to manage multiple priorities in a fast-paced environment.
- Communication: Excellent verbal and written communication skills, with the ability to convey complex technical information to diverse audiences.
- Leadership: Demonstrated leadership skills and experience managing cross-functional teams.
Benefits Extracted with AI
- Innovation & Technology
- Leadership Exposure
- Agile Environment
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