Lead Data Scientist

Who We Are Fulcrum Digital is an agile and next-generation digital accelerating company providing digital transformation and technology services right from ideation to implementation. These services have applicability across a variety of industries, including banking & financial services, insurance, retail, higher education, food, healthcare, and manufacturing. We are seeking a highly experienced Senior Site Reliability Engineer to join our Platform Engineering team. This role is pivotal in ensuring the resilience, performance, and operational excellence of our enterprise-grade virtualised application estate. The ideal candidate brings deep DevOps heritage — spanning both build and run phases — and excels at driving automation at scale across CI/CD pipelines, infrastructure provisioning, and operational tooling. Requirements This job independently executes key elements of projects/processes within the Data Science area by applying in-depth knowledge of their discipline and area best practices to effectively resolve problems and roadblocks as they occur. • Designs, develops, and reviews scalable machine learning models and statistical solutions to address complex business challenges, ensuring alignment with organizational standards. • Refines and optimizes models through advanced feature engineering, hyperparameter tuning, and validation to ensure high performance and robustness. • Collaborates with cross-functional teams, including AI/ML Engineering, to support model deployment, scaling, and operationalization. • Provides technical guidance and mentorship to junior team members, reviewing their work for quality and best practices. • Translates complex data insights into strategic recommendations for senior leadership, supporting decision-making and innovation. • Contributes to the development of best practices, standards, and knowledge sharing within the team. • Documents models, processes, and methodologies to ensure reproducibility and ongoing improvement. • May contribute to solution development for new products/services and/or manage smaller project/initiatives as an experienced individual contributor with specialized knowledge within the Data Science area.