5.0 - 9.0 years

0 Lacs

bhubaneswar

On-site

As a Senior Statistician at Rhythm, you will play a crucial role in leading statistical research, designing experiments, and developing predictive models to ensure robust data-driven insights. Your responsibilities will involve collaborating closely with data scientists, AI engineers, and business stakeholders to build scalable and interpretable statistical models that support Rhythm Innovations" AI initiatives. Your expertise in statistical methodologies and machine learning will be instrumental in enhancing the accuracy, reliability, and fairness of AI-driven solutions. Analyzing customer data to identify patterns, establish correlations, and derive actionable insights to enhance AI solutions will be a key aspect of your role. You will also develop and apply advanced statistical methodologies to analyze large-scale datasets and improve AI model accuracy. Designing and implementing rigorous experiments such as A/B testing, hypothesis testing, and Bayesian inference will be essential to validate AI models and business strategies. Collaborating with AI and machine learning teams to integrate statistical models into AI-driven applications will be a critical part of your responsibilities. Ensuring statistical integrity and robustness in AI solutions by developing methodologies for bias detection, uncertainty quantification, and explainability will also be a key focus area. Additionally, you will lead research initiatives on new statistical approaches to enhance AI fairness, reliability, and efficiency. Communicating complex statistical findings to both technical and non-technical stakeholders in a clear and impactful manner is an important part of this role. Staying up-to-date with the latest advancements in statistical methods, AI, and machine learning to continuously improve methodologies will also be expected. Moreover, mentoring junior statisticians and data scientists to foster a culture of statistical rigor and innovation will be a part of your responsibilities. The ideal candidate for this position should hold a Masters or Ph.D. in Statistics, Mathematics, Data Science, or a related field. A minimum of 5 years of experience in statistical modeling, experimental design, and data analysis, preferably in an AI-driven environment, is required. Proficiency in statistical programming languages such as R or Python, expertise in probability theory, Bayesian inference, regression modeling, and strong understanding of machine learning algorithms are essential qualifications. Experience working with large-scale data and cloud-based data platforms, proven ability to translate complex statistical concepts into actionable insights, excellent problem-solving and critical-thinking skills, as well as strong communication and collaboration skills are also required. Preferred qualifications include experience in AI ethics, fairness, and interpretability of machine learning models, knowledge of causal inference and advanced experimental design techniques, familiarity with deep learning frameworks like TensorFlow and PyTorch, as well as publications in peer-reviewed journals or conferences related to statistics, AI, or machine learning.,

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