Data Scientist

Job Description For more than 80 years, Kaplan has been a trailblazer in education and professional advancement. We are a global company at the intersection of education and technology, focused on collaboration, innovation, and creativity to deliver a best in class educational experience and make Kaplan a great place to work. Our offices in India opened in Bengaluru in 2018. Since then, our team has fueled growth and innovation across the organization, impacting students worldwide. We are eager to grow and expand with skilled professionals like you who use their talent to build solutions, enable effective learning, and improve students’ lives. The future of education is here and we are eager to work alongside those who want to make a positive impact and inspire change in the world around them. As a Data Scientist at Kaplan, you will play a pivotal role in driving data-informed decisions and developing cutting-edge solutions that enhance our educational products and services. You will leverage your expertise in machine learning, statistical modeling, and data analysis to extract meaningful insights from complex educational datasets. You will collaborate with product managers, engineers, and educators to identify opportunities for innovation and develop data-driven solutions that directly impact student learning and teacher effectiveness. Key Responsibilities: Develop and deploy advanced machine learning models: Design, implement, and evaluate machine learning models for tasks such as personalized learning recommendations, student performance prediction, content optimization, and educational resource analysis. Hands on experience in preparation of evaluation datasets and defining evaluation metrics for model training experiments. Conduct in-depth data analysis: Explore and analyze large datasets from various sources (e.g., student learning platforms, assessment data, user behavior logs) to identify trends, patterns, and insights that inform product development and educational strategies. Design and execute experiments: Develop and implement A/B testing and other experimental designs to evaluate the effectiveness of educational interventions and product features. Communicate insights and recommendations: Effectively communicate complex data insights and recommendations to both technical and non-technical audiences through visualizations, presentations, and reports. Collaborate with cross-functional teams: Work closely with product managers, engineers, educators, and researchers to define project goals, develop data-driven solutions, and ensure successful implementation. Stay up-to-date with the latest advancements: Continuously research and evaluate new machine learning techniques, tools, and best practices relevant to the education technology domain. Contribute to the development of data infrastructure: Work with data engineers to ensure data quality, accessibility, and scalability. Work on building products and features that use Generative AI Hybrid Schedule: 3 days remote / 2 days in office Minimum Requirements: Bachelor’s/Master's in Computer Science, Statistics, Mathematics, or a related field. 3+ years of experience as a Data Scientist, with a proven track record of developing and deploying machine learning models in a production environment. Strong proficiency in programming languages such as Python (with libraries like scikit-learn, TensorFlow, PyTorch, pandas, NumPy) and LLMs ( ChatGPT, Gemini, Llama, Claude) etc. Strong Proficiency in Transformer Architecture, Multimodality, RAG Pipelines and Prompt Engineering. Experience with statistical modeling, data mining, and machine learning algorithms. Experience in SQL and working with relational databases. Experience working with cloud platforms (e.g., AWS, GCP, Azure). Excellent communication and presentation skills, with the ability to translate complex technical concepts into clear and concise language. Strong problem-solving and analytical skills. Experience with MLOps workflow with tools such as Weights and Biases, MLFLow etc Experience in integrating model monitoring in production Passion for education and a desire to make a positive impact on student learning. Experience with educational data and learning analytics is a plus. Experience with Natural Language Processing and CNN Models is a plus. Preferred Qualifications: Publications in peer-reviewed journals or conferences related to machine learning or education technology. Experience working with large-scale educational datasets. Experience with recommender systems. Experience with time series analysis.