Senior Statistical Consultant

Senior Statistical Consultant

Trilenda · Leuven, Belgium (hybrid) · Permanent, full time

ABOUT US

Trilenda is an independent Belgian company delivering advanced analytics for regulated life sciences: applied statistics, Bayesian inference, causal modelling, AI and automation.

One senior team works behind three brands:

• esylos supports biotech, pharma and device developers on the decisions data alone will not settle, in clinical development, CMC and development strategy, using Bayesian and causal methods.

• Arlenda has provided CMC, discovery and non-clinical statistics since 2003. It publishes Enoval and Stabelity, 21 CFR Part 11 qualified software used by major pharmaceutical companies for method validation, bioassays and stability studies.

• Sanaitio helps medtech companies develop and validate AI-based medical devices.

Our team contributed to the statistical principles behind ICH Q2(R2) and USP <1033>, and founded the BAYES conference series. We are privately held, with no external shareholders.

THE ROLE

We are hiring a Senior Statistical Consultant to lead complex statistical work for our clients across the development lifecycle, from discovery and non-clinical studies to CMC and clinical trials.

You will be the client's statistical counterpart, so explaining and advising matter as much as computing. Bayesian thinking, causal reasoning and a critical interest in AI are part of everyday work here, not side projects.

Position: Senior Statistical Consultant

Location: Leuven, Belgium (MC-Square), hybrid

Contract: Permanent, full time

Experience: 5 to 10 years in applied statistics

Language: English (French or Dutch a plus)

Start date: As soon as possible

WHAT YOU WILL DO

You will design studies, run analyses and write the statistical content clients submit to regulators, in three areas.

Clinical statistics

• Design clinical studies, including rare disease and small-population trials, using Bayesian and adaptive designs and simulation to show their operating characteristics.

• Define estimands and analysis strategies in line with ICH E9(R1), and write the statistical sections of protocols, clinical investigation plans and SAPs.

• Advise on clinical development strategy and support sponsors in their interactions with the FDA and EMA.

CMC statistics

• Analytical procedure development, validation and transfer (ICH Q2(R2), ICH Q14, USP <1210>, USP <1033>).

• Stability study design and shelf-life estimation (ICH Q1), specifications and release limits.

• Design of experiments, design space, process validation and continued process verification; comparability and similarity assessments.

Discovery, non-clinical and immunogenicity

• Assay development and qualification, bioassays and relative potency (dose-response) modelling.

• Immunogenicity assay cut points and validation.

• Design, sample size and analysis of in vitro and in vivo pharmacology and toxicology studies, including statistical sections of study plans and reports.

• Screening, biomarker and high-dimensional data analysis.

Beyond client projects

• Bring your expertise to the statistical methods behind Enoval and Stabelity, with our software team.

• Train client teams and run workshops, so they build their own capability.

• Publish, present at conferences such as BAYES, and test where causal AI and machine learning add real value over established methods.

WHAT YOU BRING

You have 5 to 10 years of applied statistics in life sciences and enjoy moving between clinical, CMC and non-clinical problems.

Background

• A PhD in statistics, biostatistics or a related quantitative field is preferred; an MSc with strong relevant experience is welcome.

• Experience in a consultancy or CRO, handling several clients and projects in parallel.

Clinical statistics

• Trial design and sample size justification, including simulation of operating characteristics for Bayesian and adaptive designs.

• A good working knowledge of ICH E9(R1): estimands, intercurrent events and sensitivity analyses.

• Experience writing the statistical sections of protocols, clinical investigation plans and SAPs.

• Ability to prepare statistical input for FDA or EMA interactions, such as briefing documents and responses to questions.

CMC statistics

• Working knowledge of ICH Q2(R2), ICH Q14, ICH Q1, USP <1210> and USP <1033>, and of how they apply in practice.

• Method validation and transfer: accuracy profiles, tolerance intervals, total error and equivalence testing.

• Stability modelling and shelf-life estimation, and the setting of specifications and release limits.

• Design of experiments, response surface modelling, design space, process capability and continued process verification.

• Comparability and similarity assessments.

Discovery, non-clinical and immunogenicity

• Dose-response and nonlinear models (such as 4PL), parallelism testing and relative potency estimation.

• Mixed models, sample size and multiplicity control for in vitro and in vivo pharmacology and toxicology studies.

• Screening data analysis and hit selection, and analysis of biomarker and high-dimensional data.

• Immunogenicity assay cut point determination.

Methods and tools

• Hands-on Bayesian statistics: hierarchical models, prior elicitation and justification, borrowing of historical data, MCMC, and the ability to defend these choices to regulators.

• Fluent R, and Bayesian software such as Stan, brms, JAGS or NIMBLE.

• Ability to run simulation studies and to build reusable statistical tools, such as R packages or Shiny applications.

Consulting skills

• Ease with clients: you can frame a vague question, explain uncertainty to non-statisticians and hold your ground on methods.

• Clear written deliverables in English: reports, expert opinions, memos, slides and statistical sections of regulatory documents, including CTD Module 3.

• Autonomy with on-demand requests from several clients: scoping each question, estimating the effort and delivering on time.

• A fast learner with a real appetite for innovative methods.

NICE TO HAVE

• Experience with, or a strong interest in, causal AI: causal graphs, Bayesian networks, expert elicitation, digital twins.

• A good understanding of machine learning methods, and of how to validate them and compare them with classical statistical approaches.

• Python.

• French or Dutch.

• Publications, conference talks or teaching experience.

• Experience in consulting.

• Experience of regulatory interactions with the FDA or EMA, or of working in a GxP environment.

WHAT WE OFFER

• A permanent, full-time contract under Belgian law, with a competitive salary and benefits package including a company car and meal vouchers.

• Dedicated time for research, method development and publications.

• A training and conference budget, for events such as BAYES, PSI and the Non-Clinical Statistics Conference.

• Hybrid work from our Leuven office.

• A wide variety of problems, from rare disease biotechs to global pharmaceutical companies, and from bioassays to clinical trial design.

• A small senior team with decades of pharma experience, where your ideas reach clients and software quickly.

HOW TO APPLY

Send your CV and a short cover letter to Arnaud Monseur, Chief Scientific Officer, at arnaud.monseur@trilenda.com, with "Senior Statistical Consultant" in the subject line. We review applications as they arrive.

1. Introductory call with our Chief Scientific Officer.

2. In-depth call with case studies, with the Chief Scientific Officer or another senior member of the leadership team.

3. Meeting with the leadership team, then an offer.

We welcome applications from people of all backgrounds.