Data Science Consultant

Key Result Areas and Activities: Project Execution & Delivery Lead and contribute to the end-to-end execution of data science projects, including data discovery, cleansing, analysis, feature engineering, and model development. Design, develop, and deploy AI solutions that address business challenges and deliver measurable value. Implement complete AI/ML pipelines—from data collection and preprocessing to model training, evaluation, and deployment. Collaboration & Stakeholder Engagement Work closely with data scientists, software engineers, and domain experts to understand business requirements and translate them into scalable AI/ML solutions. Communicate technical concepts and insights effectively to both technical and non-technical stakeholders. Knowledge Sharing & Talent Development Share domain expertise in AI/ML across teams and clients, contributing to internal knowledge-building initiatives. Support recruitment, mentoring, and coaching efforts to grow talent and build capacity within the AI practice. Innovation & Capability Building Contribute to the Data Science Center of Excellence (COE) by developing reusable frameworks, templates, and best practices. Stay current with emerging trends, technologies, and methodologies in AI/ML and apply them to enhance solution offerings. Roles & Responsibilities Roles & Responsibilities: Demonstrate practical knowledge of transformer-based models and generative AI, including prompt engineering to optimize model outputs for real world applications. Proficient in statistical programming languages such as Python and R, with strong SQL skills for data manipulation and analysis. Possess a solid understanding of data architecture, pipeline development, and MLOps practices for robust model lifecycle management. Apply advanced statistical methods and machine learning algorithms, including ensemble techniques, deep learning, and NLP. Develop reusable frameworks, templates, and governance processes to support scalable and maintainable AI solutions. Utilize platforms like SageMaker, AzureML, and Dataiku for feature engineering, model training, and optimization. Communicate insights effectively using data visualization tools and align AI solutions with business processes to deliver both qualitative and quantitative value. Qualifications: Bachelor's degree in computer science, engineering, or related field (Master's degree is a plus). Demonstrated continued learning through one or more technical certifications or related methods. At least 6 years AI/ML experience with a minimum of 4 years in Python, R. Qualities: Assist senior team members in conducting workshops and discovery sessions to understand business priorities, challenges, and focus areas. Contribute to various stages of data science projects—from data exploration to model development. Work collaboratively with peers and other departments to support project goals, share insights, and learn best practices in data science and analytics. Ability to work with teams and clients across time zones Self-motivated and focused on delivering results for a fast-growing team and firm