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. (P)
• Understanding of Lean, Six Sigma or Operational Excellence methodologies. (P)
• Experience developing business cases and supporting strategic investment decisions. (P)

Experience

Qualifications

• Degree in Engineering, Operations Research, Data Science, Industrial Engineering, Mathematics, Statistics or a related discipline. (E)

Skills/Specialist knowledge

• Naturally curious and motivated to understand how complex systems operate.
• Strong systems thinker with the ability to connect data, processes, resources and outcomes.
• Highly analytical and comfortable working with imperfect or incomplete data.
• Commercially minded and focused on delivering tangible business value.
• Able to balance strategic thinking with hands-on analytical execution.
• Collaborative, pragmatic and action-oriented.
• Comfortable challenging assumptions through fact-based analysis.

Success Measures (First 12–18 Months)

• A trusted and regularly used enterprise operating model is established.
• Capacity models are available to support planning and investment decisions.
• Key operational datasets are connected and routinely used for decision-making.
• Multiple high-value business cases have been supported through robust analytics and modelling.
• Operational Excellence initiatives are prioritised and quantified using a consistent analytical framework.
• Measurable improvements in productivity, throughput, cost efficiency or capacity planning have been enabled through data-driven insights.
• The organisation has greater confidence in operational decisions because of improved visibility, modelling and analytical capability

Autolus Core Competencies

Focus on Results: Works to meet business goals set by management and leaders

Builds Trust and Relationships: Ensures trust with internal and external partners by delivering on commitments

Resilience: Has the capacity to recover quickly from difficulties; toughness

Communicates and Collaborates: Builds partnerships and works collaboratively with others to meet objectives

Autolus is committed to the protection of the personal information that we collect & process and we are fully compliant with General Data Protection Regulations (GDPR).

Autolus is committed to providing an inclusive and fair workplace for all. We are an equal opportunity employer and do not discriminate on the basis of race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other legally protected characteristic. We also provide reasonable accommodations throughout the recruitment process.

Autolus’ success is driven by equality and inclusion; we believe all voices are of equal value and must be heard. Whilst operating with focus and integrity, we are committed to improving diversity and inclusion within our business and our industry.