we strive to link individuals’ passions with their purpose, and our goal is to make a positive impact on the lives of millions through our engineering and science endeavors. As part of our team, we are seeking a data scientist who is highly motivated to assist us in supporting essential engineering and science projects at forward-thinking organizations. Establishing reliable and consultative partnerships with our clients is a crucial aspect of our business. If you possess an eagerness to collaborate with talented and knowledgeable professionals, comprehend the business difficulties our clients face, and work across teams to develop and promote the most
Requirements
Primary Roles & Responsibilities
• Design, develop, and deploy AI/ML products and services based on the customer needs.
• Design data pipelines
• Continually develops capability both against current demand and the technology/business capability roadmaps provided. • Review and integrate all application requirements, including functional, security, integration, performance, quality, and operations requirements.
• Continually improve technologies used by the team to deliver products and services to our customers.
• Implement all application requirements, including functional, security, integration, performance, quality, and operations requirements.
• Work closely with the Product Owners and Architects to develop data science products and data pipelines in Modern Data Platforms
• Work closely with the Team and provide guidance and assistance on technical issues
• Knowledge of handling unstructured, semi-structured and structured data
Required Skills
• 3+ years of data scientist experience
• Bachelor’s or master’s degree in data science or Applied Statistics or AI/ML or Relevant Specialization
• Cloud data engineering and Big Data services knowledge in Azure, AWS, or GCP
• Proficiency in Python and SQL.
• Proficiency in data analysis, building, and deploying models into production environments.
• Expertise in GenAI, LLMs, RAG, NLP, and deep learning architectures
• Familiarity with existing ML stack (scikit-learn, Tensor flow, Keras and others)
• Proficiency in MLOps, containerization, CI/CD pipelines, and cloud-native deployments (Snowflake, AWS, Azure, or GCP). • Fine-tuning models to improve accuracy rates.
• Interpersonal and verbal communication skills • Desire to work in a performance-based environment.