Founded in 1995, Pratham initially focused on providing pre-school education to children in Mumbai’s slums. Over the past 27 years, it has expanded significantly in both reach and impact, evolving into one of the largest non-profit organizations dedicated to children and youth across India. Pratham’s remarkable contributions have garnered widespread recognition, with prestigious awards including the Lui Che Woo Prize, WISE Prize for Innovation, Skoll Award for Social Entrepreneurship, the Henry R Kravis Prize in Leadership, and the CNN-IBN Indian of the Year for Public Service.
Pratham started its digital intervention with the Hybrid learning program in 400 villages of Rajasthan, Maharashtra and Uttar Pradesh in the year 2015. In 2017 with the support of Google.org and Sarva Mangal Family Trust this program expanded to over 1000 villages. The support led to the formation of core groups within Pratham which produced over 350 videos and about 70 learning games and software needed to deploy and monitor digital resources in the village communities. These resources are present in 11 regional languages and English. The digital hardware and software are currently available in various Pratham programs across 21 states with content in 11 languages including Punjabi, Assamese, Bengali, Odiya, Telugu, Tamil, Kannada, Marathi, Gujarati, Hindi, and English.
Pratham Digital is dedicated to harnessing the power of technology, artificial intelligence, and machine learning to create customized products and solutions for under-resourced communities. By strategically applying data analytics, we are committed to continuously improving program effectiveness, ensuring we meet the educational needs of these communities. For more information, please visit our website at www.pratham.org .
This position offers young & enthusiastic individuals interested in data analytics and machine learning the opportunity to facilitate the conception, design and execution of innovative solutions through data-informed strategies.
- Extracting, Cleaning and Analyzing large scale time series & textual datasets from SQL Server and other relational databases.
- Analyzing the extracted data from relational databases using NLP libraries in python.
- Synthesizing, visualizing, and communicating results:
- Dashboards, plots, interactive viz, presentations, and reports.
- Apply techniques like tokenization, normalization, and feature extraction to prepare the data for analysis.
- Apply NLP techniques to extract meaningful insights from textual data, including sentiment analysis, entity recognition, and topic modeling.
- Design and conduct experiments to test research hypotheses using appropriate statistical methods.
- Develop and deploy machine learning models for tasks like classification, regression, and clustering.
- Stay updated on the latest developments and research methodologies in data science, machine learning, and NLP.
Desired qualifications & experience
- A Degree in any Mathematics /Computer Science/Data Science/Economics or Related field.
- Technical Skills: Python, Machine Learning (Logistic Regression, Decision Tree, Naive Bayes, K-Means
- Clustering, Random forest or other ML algorithms),
- Natural Language Processing. Hands-on experience with NLP libraries like Spacy , NLTK and knowledge of relational databases and tools like SQL/MySQL.
- Work Experience: At least 1-2 years of experience in analyzing time series and text data using Python libraries.
- Self-driven and ability to take ownership of tasks.
- Ability to document and present analysis in a clear and concise manner .
- Solution-oriented with capacity for multi-project management.
- Prior experience in writing reports, creating presentations, and publishing research papers is a strong plus.
To streamline the application process, we encourage all candidates to utilize the form linked HERE. However, if you encounter any difficulties or have specific concerns, please feel free to reach out to email@example.com with the subject ‘Application for Senior Research Associate’. Early applications will be given preference.