Senior Data Architect
2 weeks ago
- Tech Visionary:
Develop and execute a comprehensive technology strategy aligned with the company's goals and objectives. Drive innovation and identify emerging technologies that can enhance our e-learning platforms.
- Product Leadership:
Lead the end-to-end product development lifecycle, from conceptualization to deployment. Collaborate with product managers, engineers, and designers to deliver high-quality, user-centric solutions.
- Platform Architecture:
Define the architecture and infrastructure of our e-learning platforms, ensuring scalability, reliability, and security. Implement best practices for cloud-based solutions, microservices, and API integrations.
- Technical Mentorship:
Provide strong technical leadership to the engineering team, fostering a culture of innovation, collaboration, and continuous improvement. Mentor team members and promote professional development.
- Data-Driven Insights:
Leverage data analytics and business intelligence tools to derive insights from user behaviour, performance metrics, and market trends. Use data-driven decision-making to optimize our products and services.
- Cybersecurity Expertise:
Implement robust security measures to protect user data and ensure compliance with relevant regulations (e.g., GDPR, COPPA). Stay updated on cybersecurity threats and implement proactive measures to mitigate risks.
- Partnership Development:
Evaluate potential technology partners and vendors, negotiate contracts, and manage relationships to support our technological needs. Collaborate with external partners to drive innovation and expand our capabilities.
- Budget Optimization:
Develop and manage the technology budget, ensuring efficient allocation of resources and cost-effective solutions. Monitor expenses and identify opportunities for optimization.
Requirements:Must-Haves:- Hands-on experience working with EEG data, including data pre-processing, feature extraction, and model development is mandatory.
- Familiarity with machine learning algorithms and tools (E.g., Python, MATLAB, TensorFlow, PyTorch) is necessary for building predictive models.
- Domain-specific knowledge: Must have done EEG research specific psychological parameters (e.g., stress, focus, cognitive load) with experience in this area or related fields.
- Proficiency in Python or MATLAB is highly desirable for EEG data analysis and machine learning.
- Familiarity with tools like MNE-Python, PyEEG, EEGLAB, or Scikit-learn is beneficial.
- Experience with TensorFlow, PyTorch, or other deep learning frameworks is advantageous.
The estimated salary for this role is $120,000 - $180,000 per year, depending on location and experience.
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