Data Scientist

We are seeking an experienced Data Scientist with strong expertise in machine learning, natural language processing (NLP), and generative AI to design, develop, and deploy enterprise-scale AI/ML solutions.

The ideal candidate will have hands-on experience building ML/NLP models using large structured and unstructured datasets, with a strong understanding of the end-to-end data science lifecycle. The role will involve working closely with cross-functional stakeholders to translate business requirements into scalable, data-driven solutions.

Responsibilities:

• Design, develop, and implement machine learning and NLP solutions for enterprise-scale applications.
• Develop and optimize supervised and unsupervised learning models, including: Data cleaning and preprocessing, exploratory data analysis, feature engineering, model selection and optimization, ensemble methods, model evaluation and performance metrics, and data and model visualization
• Build and maintain ML/NLP development pipelines leveraging large-scale structured and unstructured datasets.
• Develop solutions across areas such as Named Entity Recognition (NER), Document Classification, Document Summarization, Topic Modeling, Dialogue Systems, Sentiment Analysis, OCR, and text processing.
• Evaluate and leverage emerging generative AI and open-source foundation models for enterprise use cases.
• Design scalable, production-ready ML/NLP solutions following software engineering best practices and Agile methodologies.
• Work collaboratively with business stakeholders, technology teams, and partners across multiple lines of business.
• Analyze complex business and data problems and translate them into practical AI/ML solutions.
• Navigate and leverage enterprise data assets across multiple functions and domains.
• Communicate analytical findings, model outcomes, and recommendations effectively to both technical and non-technical stakeholders.

Requirements:

• 5+ years of professional experience as a data scientist, machine learning engineer, or in a related role.
• Bachelor's degree in computer science, data science, engineering, or a related technical field.
• 5+ years of programming experience in software development, preferably within Agile environments.
• 5+ years of hands-on Python programming experience for developing ML/NLP solutions. Experience with equivalent programming languages is a plus.
• Strong understanding of machine learning and natural language processing concepts, algorithms, and methodologies.
• Hands-on experience developing supervised and unsupervised ML/NLP models, including: Data preprocessing and cleaning, Exploratory data analysis, feature engineering, Model selection, ensemble techniques, Model evaluation and performance measurement, Data/model visualization
• Experience developing ML/NLP pipelines using large-scale structured and unstructured datasets.
• At least 2 years of experience designing and developing enterprise-scale ML/NLP solutions in one or more of the following areas: Named Entity Recognition (NER), Document Classification, Document Summarization, Topic Modeling, Dialogue Systems, Sentiment Analysis, and OCR Text Processing.
• Hands-on experience with OCR technologies/products and OCR-based text processing.
• Strong understanding of modern generative AI technologies and open-source models, with practical exposure to emerging GenAI frameworks and solutions.

Preferred / Desired Qualifications:

• Master's or bachelor's degree in computer science, data science, artificial intelligence, or a related technical discipline.
• Experience collaborating with diverse business, technology, and functional stakeholders across multiple lines of business.
• Demonstrated ability to work independently with a strong sense of ownership, accountability, and initiative.
• Highly motivated, proactive, and comfortable operating in a fast-paced environment with minimal day-to-day supervision.
• Strong critical thinking and analytical skills, with the ability to identify complex problems and develop effective solutions.
• Ability to understand, navigate, and leverage enterprise data assets across multiple business functions.
• Strong organizational skills with the ability to prioritize and manage multiple initiatives simultaneously.
• Excellent written, verbal, communication, and presentation skills.
• Strong problem-solving and analytical capabilities.
• Client-focused mindset with the ability to understand business needs and translate them into actionable data science solutions.
• Technical: Python, Machine Learning, NLP, Generative AI, Open-Source LLMs, OCR, Feature Engineering, Model Development, Model Evaluation, Structured and Unstructured Data, ML.