Associate Director, Operational Intelligence

Work with us Our team are passionate in the pursuit of excellence and in pushing the boundaries of cancer therapy and Autoimmune disease to deliver life-changing treatments to patients. Whilst working at Autolus you will enjoy a flexible, diverse and dynamic working environment which actively promotes creativity, leadership and teamwork – together we are ONE Autolus. Job Description: Job Title: Associate Director, Operational Intelligence Reports to Senior Director, Operational Excellence Department: Operational Excellence Hours: Monday – Friday Location: Stevenage About Autolus Autolus is a biopharmaceutical company, advancing innovative therapies at both clinical and commercial stages of development, focused on next-generation, programmed T cell therapies for the treatment of cancer. Using a broad suite of proprietary and modular T cell programming technologies, the company is engineering precisely targeted, controlled, and highly active T cell therapies designed to better recognize cancer cells, break down their defence mechanisms, and eliminate these cells. Autolus has a pipeline of product candidates in development for the treatment of haematological malignancies, solid tumours, and autoimmune diseases. Why Autolus Our team is passionate in the pursuit of excellence and in pushing the boundaries of cancer therapy and autoimmune diseases to deliver life-changing treatments to patients. Whilst working at Autolus you will enjoy a flexible, diverse, and dynamic working environment which actively promotes creativity, leadership and teamwork. In addition to this Autolus is proud to offer a competitive salary, performance related bonus as well as a comprehensive benefits package. Our Promise Autolus is developing complex, breakthrough therapies for a globally diverse market and equally recognises that diversity amongst our people is critical to our mission. As we draw on our differences, what we’ve experienced, and how we work, we celebrate diversity and are committed to creating an inclusive environment for all employees. Role Summary The Associate Director, Operational Analytics & Modelling will be responsible for developing and maintaining the analytical capabilities required to understand, model, optimise and improve Autolus' end-to-end operations. The role sits within the Operational Excellence team and operates at the intersection of data analytics, operational improvement, operational strategy and business improvement. The successful candidate will create integrated views of our operations by combining operational data, process maps, capacity models and financial information to support decision-making across Manufacturing, Testing, Supply Chain, Quality, MSAT, Engineering and supporting functions. This is not a traditional reporting or dashboarding role. The primary purpose is to develop models, simulations and analytical frameworks that help the organisation understand current performance, identify constraints, prioritise improvement opportunities and evaluate strategic options. The role will provide the analytical foundation for Operational Excellence initiatives, investment decisions, business cases, operating model development and long-term capacity planning. Key Responsibilities Operational Modelling and Simulation Develop, maintain and continuously improve the enterprise operating model. Build and maintain capacity models covering manufacturing, testing, logistics and supporting functions. Develop simulation models to evaluate the impact of process changes, technology implementations, automation opportunities and organisational changes. Conduct scenario planning and sensitivity analysis to support strategic decision-making. Create digital representations of value streams and operational workflows that can be integrated with operational performance data. Data Analytics & Insight Generation Extract, integrate and analyse data from operational systems including eBR, LIMS, ERP, quality systems, planning tools and equipment data sources where applicable. Develop datasets, analytical models and visualisations that support operational decision-making. Investigate operational performance drivers including cycle time, throughput, resource utilisation, deviations, productivity and cost. Identify trends, correlations and constraints that impact operational performance. Translate complex analyses into practical recommendations for business leaders. Business Cases & Decision Support Provide analytical support for strategic and operational business cases. Build cost-benefit analyses, ROI models and financial impact assessments. Model the expected operational and financial impact of proposed improvement initiatives. Support make-versus-buy decisions, technology investments, automation opportunities and capacity expansion evaluations. Partner with Finance and operational functions to validate assumptions and quantify benefits. Data Architecture, Quality & Governance Partner with Digital/IT and Quality to improve data availability, quality, integrity, and traceability across operational systems (e.g., MES, LIMS, ERP). Establish and maintain governance around key operational metrics, data sources, and modelling assumptions. Advanced Analytics & Problem Solving Lead or support deep-dive investigations into major drivers of cost, variability, cycle time, failure modes, and inefficiencies. Apply a variety of analytical approaches (statistical methods, simulation, forecasting, advanced Excel/Python techniques, etc.) to produce high-quality insights. Support the development of predictive or algorithmic models where appropriate (e.g., demand patterns, resource forecasting). Leadership & Collaboration Act as the organisation’s central point for Business Intelligence relating to operational performance. Collaborate cross-functionally with Production, Testing, Supply Chain, MSAT, Digital, Finance, and Operational Excellence to identify and deliver high-value analytic work. Translate complex analyses into clear, concise narratives for senior leadership. Demonstrated skills and competencies E – Essential P – Preferred Strong experience in operational analytics, business intelligence, process modelling, operational strategy or operational excellence. (E) Advanced Excel capability including complex modelling and scenario analysis. Strong experience with Power BI, Power Query and data visualisation tools. (E) Experience using Python, R or similar analytical tools to manipulate and analyse large datasets. (E) Demonstrated ability to build analytical models that support business and operational decision-making. (E) Strong stakeholder management and communication skills. (E) Ability to work across technical and non-technical teams and translate analytical outputs into actionable recommendations. (E) Experience in biotechnology, pharmaceuticals, advanced therapies, manufacturing or other regulated industries. (P) Familiarity with eBR, MES, LIMS, ERP and operational data architectures. (P) Experience with simulation modelling, capacity planning or operations research techniques.