Senior Data Scientist

• 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.

• Model Optimization & Performance
  

+ Evaluate and enhance existing machine learning models to improve accuracy, scalability, and performance.

+ Apply advanced techniques such as ensemble methods, deep learning, and NLP where applicable.

• 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.

• Strategic & Business Support
  

+ Support pre-sales and marketing efforts by developing point-of-views, engaging prospects, and contributing to solution design.

+ Assist in shaping organizational strategy through participation in Go-To-Market (GTM) initiatives and channel partnerships.

• 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.

• 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.
  

• 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.
  

• 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