Senior Data Scientist

1 day ago


Bangalore Division, India AuxoAI Engineering Pvt. Ltd. Full time

Job Description 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   Requirements Bachelor’s degree in Computer Science, Engineering, or related field; or equivalent work experience. Proven experience as a DevOps Engineer or similar role with hands-on expertise in AWS and Azure cloud environments. Strong proficiency in Azure DevOps, Git, GitHub, Jenkins, and CI/CD pipeline automation. Experience deploying and managing Kubernetes clusters (EKS, AKS) and container orchestration platforms. Deep understanding of cloud-native architectures, microservices, and serverless computing. Familiarity with Azure Synapse, ADF, ADLS, and AWS data services (EMR, Redshift, Glue) for data integration and analytics. Solid grasp of infrastructure as code (IaC) tools like Terraform, CloudFormation, or ARM templates. Experience with monitoring tools (e.g., Prometheus, Grafana) and logging solutions for cloud-based applications. Excellent troubleshooting skills and ability to resolve complex technical issues in production environments.



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