LEAD Engineer Analytics

Role & responsibilities:

1. Delivery Focused:
• Lead, mentor, and manage a team of developers and digital transformation specialists.
• Foster a culture of innovation, collaboration, and continuous learning within the team.
• Provide guidance on technical best practices and ensure timely delivery of projects.
2. RPA Strategy and Execution:
• Design, implement, and optimize RPA solutions to streamline finance processes such as accounts payable, reconciliation, and compliance reporting.
• Establish governance frameworks and define standards for RPA development, deployment, and maintenance.
• Collaborate with stakeholders to identify automation opportunities and prioritize initiatives.
3. Data Science and Analytics:
• Analyze complex financial data to uncover trends, risks, and optimization opportunities.
• Develop predictive models and implement machine learning algorithms to support decision-making.
• Create intuitive dashboards and data visualizations to communicate insights effectively to business leaders.
4. Generative AI (GenAI) Integration:
• Lead initiatives to integrate GenAI tools and models into finance processes to enhance decision-making and efficiency.
• Develop and implement AI-driven solutions for tasks such as report generation, fraud detection, and customer interaction.
• Stay abreast of GenAI advancements and assess their applicability in financial transformation.
5. Digital Transformation:
• Drive digital transformation initiatives by integrating RPA, AI, and analytics to modernize finance operations.
• Collaborate with cross-functional teams to define and execute a strategic digital roadmap.
• Evaluate emerging technologies to ensure the organization remains at the forefront of innovation.
6. Finance Process Optimization:
• Identify and eliminate inefficiencies in financial workflows, ensuring compliance with audit and regulatory requirements.
• Enhance the accuracy and speed of financial reporting and analysis through technology solutions.
• Reduce costs and improve decision-making through streamlined operations and advanced analytics.

Preferred candidate profile:

1. Educational Background:
• Bachelors or Master’s degree in computer science, Data Science, Finance, Business Administration, or a related field.
2. Technical Expertise:
• Hands-on experience with RPA tools such as Automation Anywhere, UiPath or Blue Prism.
• Strong programming skills in Python, R, or similar languages for data and AI applications.
• Proficiency in machine learning frameworks and tools such as TensorFlow or PyTorch.
• Familiarity with GenAI technologies like OpenAI, GPT models, or similar frameworks.
• Experience with data visualization tools like Power BI, Tableau, or QlikView.

Perks and benefits