Data Scientist

Role Overview

We are seeking a seasoned Data Scientist to architect, develop, and implement advanced analytics, machine learning (ML), and generative AI solutions aimed at addressing complex business problems. This role involves intensive collaboration with business stakeholders, project leaders, data engineers, and software development teams to transform extensive, multifaceted datasets into practical insights and deployable AI models.

Key Responsibilities

• Translate business needs into scalable analytics and AI solutions.
• Design comprehensive data science workflows including data preparation, feature engineering, model development, validation, and production deployment.
• Apply statistical analysis, machine learning, natural language processing (NLP), optimization, and simulation techniques.
• Develop predictive, classification, clustering, recommendation, and forecasting models.
• Create scalable ML models suitable for production use.
• Build analytics pipelines utilizing Python, R, and Apache Spark.
• Develop generative and agentic AI applications leveraging Large Language Models (LLMs).
• Handle deployment and management of models with Docker, Kubernetes, and MLOps best practices.
• Construct interactive visual dashboards using Tableau, Qlik, Plotly, ggplot2, and Shiny.
• Communicate and present insights to both technical teams and business stakeholders.
• Serve as a trusted consultant for AI and advanced analytics projects.

Required Qualifications and Skills

• Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Business Analytics, Artificial Intelligence, or related fields.
• Minimum of five years of experience in data science and machine learning.
• Strong proficiency in machine learning (both supervised and unsupervised), statistical analysis, feature engineering, predictive analytics, natural language processing, optimization, and simulation.
• Expertise in programming languages Python and R.
• Experience with big data technology Apache Spark.
• Familiarity with Large Language Models and generative/agentic AI technologies.
• Skilled in ML model deployment using Docker, Kubernetes, and MLOps methodologies.
• Competence in data visualization tools such as Tableau, Qlik, Plotly, ggplot2, and Shiny.
• Exceptional communication, presentation, and stakeholder engagement abilities.