Statistician

Job Overview

The Statistician will provide excellence and expertise in statistical support to the site in order to drive the application of advanced and state-of-the-art statistical principles, tools, and methodologies with the goal of improving process understanding, product quality, and compliance, as well as driving efficiency, process capability, and profitability.

Main Responsibilities

• With supervision and guidance, provide technical support to Quality, Program Management, Product Development, Process Development (Manufacturing Sciences, Analytical Sciences), Manufacturing, Manufacturing Engineering, Supply Chain, and Regulatory & Compliance with hands-on analysis of process and product data.
• Apply appropriate routine and advanced statistical methods in order to improve and to maintain optimal process control and product compliance, with limited guidance from the Senior Statistician.
• Explain and justify application of statistical methods to internal and external regulatory bodies and health authorities.
• Actively support PD activities and participate in the Global Statistics network.
• Implement LEAN strategies for data collection, data management, reporting, etc.
• Develop and lead statistics trainings to applicable departments.
• Develop and implement statistics-focused quality operating procedures, work instructions, forms, and templates.

Process development and design transfer

• Support the design of characterization, qualification, validation, test method development (TMD), test method validation (TMV), equivalence/comparability, stability studies, and other studies.
• Analyze and interpret data from characterization, qualification, validation, test method development (TMD), test method validation (TMV), equivalence/comparability, stability studies, and other studies.
• Support design and tech transfer activities by providing study designs and acceptance criteria that demonstrate comparability of transferred processes and product quality.
• Support the construction and interpretation of failure mode and effects analysis (FMEA) and fault tree analysis (FTA).
• Design experimental studies to evaluate criticality of inputs and to predict outputs with confidence. Select optimal parameters by evaluating DOE results through ANOVA, PLS regression, and other relevant models.
• Support products throughout the life cycle, from characterization à qualification à validation à commercial.

Product and process monitoring and controls

• Apply modeling and simulation techniques to define and support the process control strategy.
• Define, describe, calculate, and apply process capability indices and studies, including identifying characteristics, specifications, and tolerances.
• Distinguish between natural process limits and specification limits.
• Calculate percent defective and future risk.
• Assess processes through the implementation of monitoring and statistical process control (monitoring plans and reports, establishing commercial control limits).
• Support the compilation of Annual Product Reviews (APRs).
• Define sampling plans that are in line with the site’s sampling strategy, including defining, describing, and applying the concepts of producer and consumer risk, operating characteristic (OC) curves, acceptable quality limits (AQL), and rejectable quality limits (RQL).
• Define sampling plans that are in line with the site’s qualification sampling strategy in order to qualify and challenge process controls by establishing failure rates.

Data-driven decision making

• Select, construct, apply, and interpret tools such as flowcharts, pareto charts, cause and effect diagrams, control charts, check sheets, scatter diagrams, and histograms and support implementation.
• Support the analysis of complex data sets to facilitate root cause investigations by offering data-driven decisions.
• Calculate and interpret standard error, tolerance intervals, confidence intervals, and equivalence intervals.
• Apply and interpret the concepts of significance level, power, type I, and type II errors.
• Define and distinguish between statistical and practical significance.
• Support Key Performance Indicators (KPIs) tracking/monitoring.

Skills and Qualification

• Bachelor’s Degree required, preferably in Statistics, Mathematics, Engineering, or another relevant branch of study
• 3+ years of relevant experience
• Proven experience in data science and applied statistics, e.g., in DOE and multivariate data analysis including regression and ANOVA.
• Proficiency with statistical software, e.g., JMP, Minitab, SPSS, SAS, R.
• Proficiency in Microsoft Office (Word, Excel, PowerPoint).
• Effective communication (written and verbal) and collaboration within cross-functional teams.

We Offer

• Competitive compensation package
• Modern working environment with state-of-the-art facilities and technologies
• Challenging assignments in a fast growing and innovative industry
• Position in a dynamic, international team of highly skilled professionals
• Variety of opportunities for personal and professional development within a global organization

Please note that SHL is a drug free employer. This offer of employment is contingent upon your successful completion of various preemployment screenings, including, but not limited to, a drug test, employment verification, reference checks, and a criminal background check.

For more information on SHL Medical, please visit: shl-medical.com