Senior Associate - Data Scientist

• 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
• You will collaborate closely with cross-functional teams including business analysts, software engineers, and product managers to understand business requirements, define problem statements, and deliver scalable solutions
• Additionally, you'll be expected to stay current with emerging technologies and methodologies in the AI/ML landscape to ensure our technical approaches remain cutting-edge and effective

Desired Skills and experience

• 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.
• Proficiency in cloud platforms, such as Azure, Azure Data Factory, Snowflake, Databricks.
• Experience with data manipulation, cleaning, and preprocessing using pandas, NumPy, or equivalent libraries.
• 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.
• Experience with version control systems (e.g., Git) and collaborative development practices.
• Proficiency with visualization tools and libraries such as Matplotlib, Seaborn, Tableau, or PowerBI.
• Strong mathematics background including statistics, probability, linear algebra, and calculus.
• Excellent communication skills with ability to translate technical concepts to non-technical stakeholders.
• Experience working in cross-functional teams and managing projects through the full data science lifecycle.
• 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.
• Collaborate with cross-functional teams to understand business requirements and translate them into analytical solutions.
• Evaluate model performance using appropriate metrics and validation techniques to ensure reliability and robustness.
• Present findings, visualizations, and recommendations to stakeholders in clear, accessible formats tailored to technical and non-technical audiences.
• Stay current with the latest advancements in machine learning, deep learning, and statistical methods through continuous learning and research.
• Develop proof-of-concept applications to demonstrate the value and feasibility of data science solutions.
• Implement A/B testing and experimental design methodologies to validate hypotheses and measure the impact of implemented solutions.
• Document methodologies, procedures, and results thoroughly to ensure reproducibility and knowledge transfer within the organization.