Job Title

We are seeking a skilled and motivated Data Scientist with 2-5 years of experience to join our team. The successful candidate will develop and enhance machine learning (ML) models to analyze user interaction data collected through a mobile game application. This role will also involve incorporating additional data sources, such as facial expressions and gaze data from video content.Key ResponsibilitiesModel Development: Design, develop, and implement machine learning models to process and analyze finger kinetics data collected from a mobile game application.Data Analysis: Perform exploratory data analysis to identify patterns and insights from user interaction data, ensuring high-quality model inputs.Research & Innovation: Collaborate with cross-functional teams to research and integrate facial expression and gaze data from video content to enhance model performance and application capabilities.Model Optimization: Optimize ML models for accuracy, scalability, and efficiency, ensuring robust performance in a production environment.Data Pipeline Development: Build and maintain data pipelines to process and transform raw data into formats suitable for model training and evaluation.Experimentation: Conduct experiments to test hypotheses, validate model performance, and iterate on model designs based on results.Collaboration: Work closely with software engineers, product managers, and domain experts to integrate ML models into the game application and ensure seamless functionality.Documentation: Document model development processes, research findings, and technical specifications to support team collaboration and knowledge sharing.QualificationsEducation: Bachelor’s or master’s degree in computer science, Data Science, Statistics, Mathematics, or a related field.Experience: 2-5 years of experience in data science, machine learning, or a related role, preferably in a health tech or consumer-facing application environment.Technical Skills:Proficiency in Python or R for data analysis and model development.Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.Familiarity with data processing tools and libraries (e.g., pandas, NumPy).Knowledge of computer vision techniques for analyzing facial expressions and gaze data is a plus.Understanding of statistical methods and data visualization tools (e.g., Matplotlib, Seaborn).Soft Skills:Strong problem-solving skills and a curiosity-driven approach to research.Excellent communication skills to present complex technical concepts to non-technical stakeholders.Ability to work collaboratively in a fast-paced, interdisciplinary team environment.Nice-to-Have:Experience with mobile application data or health-related datasets.Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) for model deployment.Knowledge of experimental design and A/B testing methodologies.