AllSTEM Connections is actively recruiting on behalf of one of our valued clients, a leading organization recognized for innovation, scientific advancement, and operational excellence within the life sciences industry. We are excited to present this opportunity to professionals who are passionate about statistical analysis, experimental design, process development, and cross-functional collaboration. If this opportunity aligns with your background and career goals, we encourage you to apply and take the next step in joining a dynamic and highly collaborative team.
Position Summary
We are seeking a highly motivated
Statistician II / DOE Process Development Scientist
to support critical process development and characterization projects. This is a hands-on, project-facing role where you will partner closely with scientists and engineers to design experiments, perform statistical analyses, interpret complex data, and provide actionable recommendations that drive process improvements.
The ideal candidate will bring strong expertise in
Design of Experiments (DOE)
,
JMP
, and advanced statistical methodologies, along with experience supporting projects within regulated life sciences environments such as pharmaceutical, biopharmaceutical, biotechnology, or medical device organizations.
Position Details
Hourly Pay Rate (W2):
$67.30 - $76.90/hr
Contract Duration:
Through January 18, 2027
Work Arrangement:
100% Remote
Employment Type:
Contract (W2)
Top Must-Haves
Design of Experiments (DOE) experience
Advanced JMP software expertise
Statistical analysis and experimental design experience
Process Development and/or Process Characterization experience
Pharmaceutical, Biopharmaceutical, Biotechnology, or Medical Device industry experience
Master's Degree or PhD in Statistics, Biostatistics, Chemical Engineering, Industrial Engineering, or related field
Strong collaboration and communication skills
Key Responsibilities
Design and develop studies using
Design of Experiments (DOE)
methodologies for process development and characterization projects.
Perform statistical analyses and generate reports utilizing
JMP
and other statistical software tools.
Collaborate with Process Scientists and Engineers to define study objectives, experimental constraints, and project requirements.
Analyze experimental data and communicate findings, recommendations, and conclusions to technical stakeholders.
Support process characterization and process optimization initiatives through data-driven decision-making.
Develop and maintain technical reports, presentations, and statistical documentation.
Participate in cross-functional project teams and provide statistical expertise throughout the project lifecycle.
Deliver high-quality work in a fast-paced environment while maintaining strong attention to detail.
Required Qualifications
Education
Master's degree in
Statistics, Biostatistics, Chemical Engineering, Industrial Engineering
, or a related discipline with at least 2 years of relevant experience; OR
PhD in a related discipline with at least 1 year of relevant experience.
Required Skills & Experience
Proven experience applying
Design of Experiments (DOE)
to real-world process development challenges.
Strong expertise with
JMP
software.
Solid understanding of statistical analysis methodologies and experimental design principles.
Experience working with multidisciplinary scientific and engineering teams.
Strong analytical, problem-solving, and critical-thinking abilities.
Excellent verbal and written communication skills.
Ability to work effectively in a remote and collaborative environment.
Strong organizational skills with exceptional attention to detail.
Preferred Qualifications
Experience within the
Pharmaceutical
,
Biopharmaceutical
,
Biotechnology
, or
Medical Device
industries.
Prior experience supporting
Process Development
or
Process Characterization
initiatives.
Familiarity with Minitab or other statistical software platforms.
Background in Chemical Engineering or Industrial Engineering.
Industry internship, co-op, or direct commercial experience within regulated environments.