Acuity Knowledge Partners is hiring multiple Senior Data Scientist for its Data and Technology Services Team for Pune 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 [Confidential Information]
