Senior Data Scientist

3 weeks ago

Bengaluru, India Acuity Knowledge Partners Full time

Acuity Knowledge Partners is hiring multiple 'Senior Data Scientist ' for its Data and Technology Services Team for Bengaluru location (hybrid: 2-3 days WFO). " As a key member of our Data Science team, you will be responsible for developing innovative AI & ML solutions across diverse business domains. This includes designing, implementing, and optimizing advanced analytics models to address complex business challenges and drive data-driven decision making. Your core responsibility will be to extract actionable insights from large datasets, develop predictive algorithms, and create robust machine learning pipelines" 'Immediate Joiners are highly preferred ' - Bachelors or master’s in science or engineering disciplines (Computer Science, Engineering, Math's, Physics, etc.) or a related field Required Key Skills: 5 to 12 years of demonstrated expertise in applying advanced statistical modeling, machine learning algorithms, and deep learning techniques. Proficiency in programming languages such as Python data analysis and model development and also in cloud platforms, such as Azure, Azure Data Factory, Snowflake, Databricks, etc. Strong knowledge of SQL and experience working with various database systems and big data technologies. Proven track record of developing and deploying machine learning models in production environments. Strong mathematics background including statistics, probability, linear algebra, and calculus. Excellent communication skills with ability to translate technical concepts to non-technical stakeholders. Knowledge of ethical considerations in AI development including bias detection and mitigation techniques. Key Responsibilities: Analyze complex datasets to extract meaningful insights and patterns using statistical methods and machine learning techniques. Design, develop and implement advanced machine learning models and algorithms to solve business problems and drive data-driven decision making. Perform feature engineering, model selection, and hyperparameter tuning to optimize model performance and accuracy. Create and maintain data processing pipelines for efficient data collection, cleaning, transformation, and integration. Evaluate model performance using appropriate metrics and validation techniques to ensure reliability and robustness. Implement A/B testing and experimental design methodologies to validate hypotheses and measure the impact of implemented solutions. Develop proof-of-concept applications to demonstrate the value and feasibility of data science solutions. Stay current with the latest advancements in machine learning, deep learning, and statistical methods through continuous learning and research. Interested candidates, please share your updated CV at

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