Senior Software Engineer: Data Science & Optimisation

About the role:

For our Customer Experience team, we seek Hands-On Senior Data Scientist who can work on designing & implementing high quality scalable optimization-based applications and platforms, while providing technical leadership and mentoring to a small team of talented developers in agile environment. Your ability to take ownership of architecture, design, and implementation of maintainable, high-quality, and high-performing Machine Learning systems and Optimization applications is essential for success in this role.

Provide hands-on technical expertise to design, engineer, deploy, and deliver highly scalable optimization-based applications. Drive improvements in technical architecture, standards, and processes. Drive engineering excellence while managing/mentoring talented team of developers in agile environment. Work closely with product management and other stakeholders for system design and delivery.

What you will d0 

As an Optimization and AI/ML Expert, you will be responsible for developing and implementing advanced machine learning models, optimization algorithms, and analytical tools. You will leverage your expertise to solve complex business problems by using data-driven approaches and predictive modelling techniques. The ideal candidate will have a strong background in AI/ML, optimization, and applied mathematics, with a passion for designing efficient solutions to tackle large-scale, real-world challenges.

Who you are and what you bring

• Optimization & AI/ML Model Development: Design, develop, and implement AI/ML models and optimization algorithms to address business challenges and improve decision-making.
• Data Analysis & Feature Engineering: Work with large datasets to preprocess, analyze, and engineer features for model development. Ensure data quality and integrity.
• Performance Improvement: Apply optimization techniques (e.g., linear programming, constraint programming, heuristic algorithms) to optimize business operations, resource allocation, and other key processes.
• Collaboration & Problem-Solving: Collaborate with cross-functional teams, including data engineers, business analysts, and domain experts, to identify problems and translate them into solvable AI/ML models.
• Research & Innovation: Stay updated on the latest trends in optimization, machine learning, and AI research. Evaluate and apply emerging technologies and techniques to enhance system performance.
• Model Evaluation & Tuning: Conduct model evaluation using appropriate metrics, tune hyperparameters, and ensure that models perform optimally in production environments.
• Documentation & Reporting: Document the methodology, processes, and results of AI/ML projects. Communicate findings to stakeholders and contribute to technical reports or presentations.
• Deployment & Monitoring: Work with engineering teams to deploy AI/ML models into production. Monitor model performance and provide ongoing support for scalability and robustness.
• Experience: 5-10 years of experience in AI/ML, optimization, and data science with a proven track record of applying these skills to real-world business challenges.
• Strong Analytical Skills: Expertise in quantitative analysis, applied mathematics, and optimization algorithms (e.g., integer programming, dynamic programming, convex optimization).
• Proficiency in Programming: Strong programming skills in Python, R, and/or MATLAB. Experience with libraries like TensorFlow, PyTorch, Scikit-learn, or similar.
• Machine Learning Expertise: Deep understanding of supervised and unsupervised learning, reinforcement learning, and model validation techniques. Familiarity with deep learning and neural networks is a plus.
• Optimization Knowledge: Solid knowledge of optimization techniques for solving complex resource allocation, scheduling, or routing problems.
• Data Handling & Analysis: Experience with big data technologies (Hadoop, Spark), data preprocessing, and feature engineering techniques.
• Problem-Solving Mindset: Ability to translate business problems into mathematical models and find creative solutions.
• Communication Skills: Strong written and verbal communication skills to effectively convey technical concepts to non-technical stakeholders.
• Advanced Degree: A Master's or Ph.D. in Computer Science, Mathematics, Engineering, Operations Research, or a related field is highly desirable.

Preferred Qualifications

• Experience in the deployment and scaling of AI/ML models in production environments.
• Knowledge of cloud platforms such as AWS, Google Cloud, or Azure.
• Familiarity with optimization software/tools like Gurobi, CPLEX, or other commercial solvers.
• Experience with reinforcement learning and optimization in dynamic or uncertain environments.