Data Scientist

Company Description NEMA AI delivers artificial intelligence–driven neurotechnology solutions that combine advanced EEG-based brain signal analysis with clinical intelligence. The organization focuses on early detection and continuous monitoring of cognitive decline and neurological disorders by identifying subtle changes in brain function before symptoms become severe. Its platform enables real-time, objective brain health assessment to help clinicians make faster and more accurate decisions. Through proprietary technology and clinical integration, NEMA AI strives to make brain health screening accessible, scalable, and effective across healthcare systems worldwide. Team members contribute to a mission-oriented environment at the intersection of healthcare, neuroscience, and AI.

Role Description The Data Scientist will support the development and refinement of NEMA AI’s brain health analytics by working with EEG and clinical data in a hybrid setting based in South Delhi, with some work from home flexibility. Day-to-day responsibilities include cleaning, organizing, and analyzing structured and unstructured datasets, building and validating statistical and machine learning models, and generating insights to improve early detection of cognitive decline and neurological disorders. The role involves collaborating with clinicians, engineers, and researchers to translate data findings into actionable product features and decision-support tools, as well as designing experiments and performance metrics to evaluate model effectiveness. The Data Scientist will also create clear visualizations and documentation to communicate results to both technical and non-technical stakeholders and may support publication, reporting, and presentation efforts related to neuroscience and AI research.

Qualifications

• Strong foundation in Data Science and Statistics, with the ability to design experiments, choose appropriate models, and evaluate performance.
• Proficiency in Data Analytics and Data Analysis for handling real-world healthcare datasets, including preprocessing, feature engineering, and exploratory analysis.
• Experience in Data Visualization to clearly communicate complex findings using dashboards, charts, and reports.
• Hands-on skills with programming languages and tools commonly used in data science (e.g., Python, R, SQL, Jupyter, relevant libraries such as pandas, scikit-learn, NumPy, Matplotlib, or Plotly).
• Knowledge of machine learning workflows; familiarity with time-series or signal processing methods is a plus, especially for EEG or clinical data.
• Ability to work collaboratively in a multidisciplinary team, with clear written and verbal communication across technical and clinical stakeholders.
• Relevant academic background in a quantitative field such as Data Science, Computer Science, Statistics, Engineering, Neuroscience, or a related discipline; ongoing students or recent graduates are welcome.
• Interest in brain health, neurotechnology, and applying AI to healthcare challenges; prior experience with healthcare or biomedical data is beneficial.