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.

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Qualifications:

• Bachelors degree in computer science, engineering, or related field (Masters 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