AuxoAI - Senior Data Scientist - Machine Learning

<p><p><b>Job Description :</b><br/><br/>AuxoAI is seeking a Senior Data Scientist with deep expertise in advanced algorithms and scientific rigor to lead strategic initiatives.<br/><br/> In this role, youll apply machine learning, causal inference, Bayesian methods, and statistical modeling to solve high-impact business problems and guide AI-native product development.<br/><br/> This position is ideal for someone who combines technical depth with curiosity and discipline, and enjoys mentoring others while translating complexity into clarity.<br/><br/><b>Location :</b> Mumbai/Bengaluru/Hyderabad/ Gurgaon (Hybrid) <br/><br/><b>Responsibilities :</b><br/><br/>- Lead the design and development of algorithms across ML, causal inference, and AI problem spaces <br/><br/>- Conduct exploratory data analysis, feature engineering, and statistical modeling with an emphasis on interpretability and reproducibility <br/><br/>- Benchmark and optimize models using advanced algorithms such as gradient boosting (XGBoost/LightGBM), survival analysis, Bayesian hierarchical models, causal impact analysis, and probabilistic graphical models <br/><br/>- Translate complex models into clear, scalable solutions in collaboration with engineering and product teams <br/><br/>- Establish best practices for experimentation, validation frameworks, and responsible AI across projects <br/><br/>- Mentor junior data scientists and foster a high-standard, knowledge-sharing environment <br/><br/>- Stay up to date with emerging techniques in optimization, causal inference, reinforcement learning, bandits, and MCTS <br/><br/><b>Requirements :</b><br/><br/>- 6+ years of experience delivering production-grade statistical and machine learning solutions <br/><br/>- Strong foundation in hypothesis testing, Bayesian inference, and experimental design <br/><br/>- Proven experience with classical ML algorithms, including boosted trees, GLMs, survival models, and ensemble methods <br/><br/>- Proficient in Python and key libraries such as pandas/Polars, scikit-learn, and StatsModels <br/><br/>- Demonstrated ability to turn ambiguous business questions into measurable statistical models <br/><br/>- Ability to communicate insights effectively to both technical and non-technical audiences <br/><br/>- Exposure to MLOps tools and cloud-based environments is a plus <br/><br/>- Advanced degree (M./Ph.) in Statistics, Computer Science, or a related field</p><br/></p> (ref:hirist.tech)