Data Science & AI/ML

Overview

As a Data Scientist / AI/ML Engineer at SysMind, you’ll be at the center of transforming data into intelligent solutions that drive measurable business value. You’ll work across the data and AI lifecycle to build predictive models, machine learning solutions, and AI-powered applications that solve complex business challenges.

The role demands a blend of analytical thinking, technical expertise, curiosity, and creative problem-solving. You’ll collaborate closely with data engineers, software developers, architects, and business stakeholders to define data strategies, develop scalable models, and deploy reliable AI solutions.

Your focus will be on turning complex datasets into actionable insights and intelligent systems, ensuring our solutions are accurate, scalable, explainable, and production-ready.

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Roles & Responsibilities

• Develop and implement machine learning and AI models for prediction, classification, recommendation, forecasting, and optimization.
• Analyze large and complex datasets to identify patterns, trends, anomalies, and actionable business insights.
• Design and maintain data science workflows covering data preparation, feature engineering, model development, validation, and deployment.
• Use technologies such as Python, SQL, Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, and modern AI/ML frameworks.
• Develop solutions leveraging Generative AI, Large Language Models (LLMs), NLP, computer vision, and AI agents where applicable.
• Collaborate with engineering and product teams to translate business requirements into data-driven solutions and measurable outcomes.
• Build and evaluate models using appropriate metrics, validation techniques, experimentation, and statistical methods.
• Implement MLOps practices for model versioning, monitoring, retraining, deployment, and lifecycle management.
• Integrate AI/ML solutions into applications and CI/CD pipelines to support reliable production deployment.
• Perform exploratory data analysis, statistical analysis, and root-cause investigation to support business and technical decisions.
• Monitor model performance, data quality, drift, bias, and reliability, driving continuous improvement and corrective actions.
• Ensure AI solutions follow responsible AI, security, privacy, explainability, and governance standards.
• Collaborate with cross-functional teams to promote a data-driven and AI-first culture across the organization.

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If you believe the future of technology is built on data, intelligence, and innovation, and you’re passionate about solving real-world problems with AI and machine learning, apply to join SysMind’s Data Science & AI/ML engineering team.

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