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