NNIIT | Chief Data Scientist | india

7 hours ago

india NNIIT Full time

Chief Data Scientist (CTO)

Location: Hyderabad(Begumpet - Onsite)

Languages: English and Hindi (if Telugu, then it would be an added advantage)


Position Overview:

We are seeking an experienced Chief Data Scientist (CTO) to lead our technological vision and innovation in the e-learning industry. As the CDS, you will be responsible for overseeing all aspects of our technological development, ensuring that our platforms are cutting-edge, scalable, and user-friendly. You will work closely with cross-functional teams to drive product development, technology strategy, and digital transformation initiatives. This role requires a strong blend of technical expertise, strategic thinking, and leadership skills.



Mandatory Experience Required:

  • EEG data analysis: You should have hands-on experience working with EEG data, including data pre-processing, feature extraction, and model development is mandatory.
  • Machine learning: 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.


Mandatory Skills and Tools Required:

  • Programming languages: Proficiency in Python or MATLAB is highly desirable for EEG data analysis and machine learning.
  • Data analysis tools: Familiarity with tools like MNE-Python, PyEEG, EEGLAB, or Scikit-learn is beneficial.
  • Machine learning frameworks: Experience with TensorFlow, PyTorch, or other deep learning frameworks is advantageous.



Key Responsibilities:

1. Technology Strategy: 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.


2. Product Development: 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.


3. 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.


4. Technical Leadership: Provide strong technical leadership to the engineering team, fostering a culture of innovation, collaboration, and continuous improvement. Mentor team members and promote professional development.


5. Quality Assurance: Establish processes and standards for quality assurance and testing to ensure the reliability and performance of our platforms. Implement automated testing frameworks and DevOps practices.


6. Data Analytics: 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.


7. Security and Compliance: 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.


8. Partnerships and Vendor Management: 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.


9. Budget Management: Develop and manage the technology budget, ensuring efficient allocation of resources and cost-effective solutions. Monitor expenses and identify opportunities for optimization.

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