Senior Scientist - Statistical Process Control (SPC) & Data Analytics

Sokolservices; Madison (NJ); Hybrid; USD 77,000 - 84,000; Full time

Benefits offered by this job

Health insurance with dental andVision

Holiday pay

401(k) program

Employee referral bonus program

Job summary

Sokolservices seeks a Senior Scientist in Madison, NJ to lead Statistical Process Control and data analytics for a Global MSAT team. The role involves hands-on data prep, statistical analysis, and coding to improve processes and reporting.

The ideal candidate has GMP pharma experience, 5+ years in data analytics, and proficiency in R or Python. Hybrid onsite work with travel up to 10% and a 6-month W‑2 contract is offered.

Qualifications

• Bachelor's degree in Life Sciences, Biotechnology, Engineering, Statistics, Data Science, or related discipline.
• 5+ years of pharmaceutical GMP experience.
• 3+ years in data management and analytics.
• Hands-on coding experience using R or Python for data preparation and reporting.
• Ability to assess data completeness and prepare reliable datasets for statistical analysis.
• Experience applying SPC, process monitoring, capability analysis, or comparative statistics.

Responsibilities

• Prepare, clean, merge, validate, and analyze manufacturing and quality datasets using R or Python.
• Apply SPC, control charts, process capability analysis, and comparative statistical methods.
• Monitor process performance, identify trends, investigate statistical alerts, and communicate findings.
• Execute routine and ad hoc analyses and prepare reports and presentations for stakeholders.
• Improve analytical tools, data preparation workflows, and reporting processes through coding and automation.
• Support CPV and APQR activities.
• Contribute to analytical system configuration, technical documentation, and process improvements.
• Collaborate with MSAT, Manufacturing, Quality, and other cross-functional stakeholders.

Skills

Analytical thinking

Problem solving

Technical communication

Cross-functional collaboration

Statistical reasoning

Education

Bachelor's degree in Life Sciences/ Biotechnology/ Engineering/ Statistics/ Data Science

Tools

R

Python

Job description

We are looking for a Senior Scientist specializing in Statistical Process Control (SPC) and Data Analytics to support a Global Manufacturing Science & Technology (MSAT) team within the pharmaceutical industry.

This role combines hands‑on data preparation, applied statistical analysis, and coding to support manufacturing process monitoring, reporting, and continuous improvement. The ideal candidate is comfortable working with R or Python, preparing and validating datasets, applying statistical methods, and improving analytical workflows. Experience with AI-assisted coding tools is welcome.

Key Responsibilities:

• Prepare, clean, merge, validate, and analyze manufacturing and quality datasets using R or Python;
• Apply statistical process control (SPC), control charts, process capability analysis, and comparative statistical methods;
• Monitor process performance, identify trends, investigate statistical alerts, and communicate findings;
• Execute routine and ad hoc analyses and prepare reports and presentations for stakeholders;
• Improve analytical tools, data preparation workflows, and reporting processes through coding and automation;
• Support Continued Process Verification (CPV) and Annual Product Quality Review (APQR) activities;
• Contribute to analytical system configuration, technical documentation, and process improvements;
• Collaborate with MSAT, Manufacturing, Quality, and other cross-functional stakeholders.

Position details:

• Hourly rate: $55.80–$60.80;
• Contract length: Initial 6 months with possible extension, subject to client needs and budget approval;
• Location: Madison, NJ 07940 (Giralda Farms);
• Work arrangement: Hybrid, 50% onsite with flexible onsite days;
• Schedule: Monday–Friday, 9 AM–5 PM EST, with core hours of 10 AM–4 PM EST;
• Maximum hours: 40 hours per week;
• Travel: Up to 10% globally;
• W-2 contract position;
• No C2C options;
• No visa sponsorship.

Required:

• Bachelor's degree in Life Sciences, Biotechnology, Engineering, Statistics, Data Science, or a related discipline;
• 5+ years of pharmaceutical experience in a GMP-regulated environment;
• 3+ years of experience in data management and analytics;
• Hands‑on coding experience using R or Python for data preparation, manipulation, analysis, or reporting;
• Ability to assess data completeness, identify inconsistencies, and prepare reliable datasets for statistical analysis;
• Practical experience applying statistical methods, including statistical process control (SPC), process monitoring, capability analysis, or comparative statistics;
• Demonstrated project experience applying coding and statistical analysis to real business or technical problems;
• Strong analytical thinking, problem‑solving, and technical communication skills;
• Ability to collaborate with cross‑functional stakeholders and work effectively within a matrix team;
• Authorization to work in the United States without visa sponsorship.

Preferred:

• Experience in pharmaceutical manufacturing, process development, analytical development, or MSAT;
• Experience with Continued Process Verification (CPV) and Annual Product Quality Review (APQR);
• Experience supporting statistical process monitoring in commercial cell therapy or biopharmaceutical manufacturing;
• Experience with JMP, Minitab, or other statistical analysis software;
• Experience with control charts, Shewhart charts, Western Electric rules, t-tests, or Wilcoxon tests;
• Experience with coding automation or AI-assisted coding tools;
• Experience developing or improving analytical reporting systems;
• Knowledge of GMP requirements and pharmaceutical manufacturing processes;
• Experience with matrix leadership, project coordination, or stakeholder negotiation.

• Health insurance with dental and vision insurance options.
• Holiday pay.
• 401(k) program.
• Employee referral bonus program.
• The client retains the right to hire the contractor directly.