Key Responsibilities

• Design and implement predictive models and machine learning algorithms to solve business problems, including text classification, regression models, and other statistical techniques.
• Develop and implement NLP techniques to automate manual document review processes, such as text classification, sentiment analysis, and named entity recognition.
• Work with large datasets to mine useful insights and present findings using data visualization techniques, ensuring that results are actionable and aligned with business goals.
• Collaborate with cross-functional teams (business analysts, product managers, and engineers) to define data requirements, understand use cases, and translate them into analytical solutions.
• Develop tools and processes for monitoring model performance in production environments, ensuring that models remain accurate and effective over time.
• Assess the effectiveness of new data sources, techniques, and tools, ensuring high data quality and consistency. Maintain proper documentation and governance of all models.
• Provide clear, well-documented explanations of model behavior, assumptions, and limitations. Communicate findings to stakeholders through presentations and reports.
• Stay up to date with the latest trends and techniques in machine learning, NLP, and data science to continuously improve model accuracy, efficiency, and innovation.

Required Skills

• Strong experience in applying machine learning algorithms (supervised and unsupervised learning), including regression analysis, hypothesis testing, and predictive modeling.
• Proficient in NLP techniques for text classification, sentiment analysis, and document automation.
• Strong proficiency in Python and/or R for data analysis and model development.
• Experience with popular machine learning libraries and frameworks such as pyTorch, TensorFlow, scikit-learn, and similar tools.
• Proficient in SQL for data extraction and manipulation from relational databases.
• Strong foundation in applied mathematics, statistics, and statistical modeling.

Preferred Skills/Qualifications

• Familiarity with model governance processes, model validation, and maintaining comprehensive documentation of models.
• Exposure to large language models (e.g., GPT, BERT) and their application in NLP tasks.
• Familiarity with machine learning product system design, ensuring that models integrate well into production environments and can scale efficiently.
• trong ability to visualize and communicate complex data and model results using tools like Matplotlib, Seaborn, Tableau, or similar.
• Bachelor's or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.

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