Company Overview
[$COMPANY_OVERVIEW]
Role Overview
[$COMPANY_NAME] is hiring a Senior Time Study Technologist to design, lead, and operationalize rigorous work measurement and task analysis programs that drive productivity, ergonomics, and process standardization across manufacturing and field operations in [$COMPANY_LOCATION]. In this senior individual contributor / technical lead role you will architect end-to-end time study methodologies, implement sensor- and video-based data collection systems, analyze high-resolution cadence data using statistical and machine learning methods, and partner with industrial engineering, operations, safety, and product teams to convert measurement insights into sustainable process change.
Responsibilities
- Design and own enterprise-grade time study programs: sampling plans, stopwatch and video protocols, inter-rater reliability (IRR) procedures, and documentation of Predetermined Motion Time Systems (PMTS) where applicable.
- Lead end-to-end data collection projects using mixed modalities (manual time study, video annotation, wearable IMUs, RFID/UWB, PLC/event logs, and computer vision) to measure takt time, cycle time, setup, transfer, and non-value-added time.
- Develop and validate measurement systems: create scoring rubrics, train analysts, run IRR assessments, and maintain measurement error budgets and confidence intervals for key metrics.
- Implement and maintain tooling for data capture and processing: design ETL pipelines, automate annotation workflows, and integrate time-stamped sensor data with ERP/MES and workstation logs.
- Perform advanced analysis: time series analysis, survival analysis for task durations, Bayesian models for small-sample inference, and ML-based activity recognition to derive actionable KPIs.
- Produce reproducible deliverables: clear statistical reports, dashboards (Tableau/Power BI), reproducible Jupyter/R Markdown notebooks, and architecture decision records (ADRs) for measurement choices.
- Influence cross-functional strategy: present findings to senior leadership, translate measurement outcomes into capacity planning, workforce forecasting, line balancing, and automation investment recommendations.
- Mentor and upskill junior time study technicians and industrial engineers: develop training materials, lead workshops, and establish best-practice playbooks.
- Ensure compliance with data privacy, safety, and change management: manage video consent processes, anonymization, and collaborate with EHS to mitigate ergonomic risk during studies.
Required and Preferred Qualifications
Required:
- 7+ years of professional experience in time study, work measurement, industrial engineering, operations research, or equivalent, with multiple end-to-end projects delivered in production environments.
- Deep knowledge of work measurement methodologies (time study, PMTS, MTM/Maynard, REFA or equivalent) and demonstrated ability to design statistically valid sampling schemes.
- Proven experience deploying and validating mixed-modality data collection (video-based observation, stopwatch, sensors/IMUs, RFID/UWB, PLC/event logs).
- Strong quantitative background: experience with statistical inference, time series analysis, and modeling uncertainty in duration estimates.
- Proficiency in at least one programming language for analysis (Python or R) and SQL for data extraction and transformation.
- Experience building reproducible analysis artifacts (Jupyter, R Markdown) and automated ETL pipelines into visualization tools (Tableau, Power BI, or equivalent).
- Track record of leading stakeholders, producing clear business recommendations, and driving cross-functional change.
Preferred:
- Experience with computer vision and activity recognition (OpenCV, TensorFlow, PyTorch) for automated annotation and task segmentation.
- Familiarity with manufacturing execution systems (MES), PLC data, and ERP integration for correlating time studies with production metrics.
- Experience with cloud data platforms (AWS/GCP/Azure), streaming ingestion (Kafka), and containerized tooling (Docker, Kubernetes).
- Certification in industrial engineering, Six Sigma Black Belt, Certified Motion Analyst, or equivalent professional credentials.
- Prior experience operationalizing time-study programs at scale in high-mix or high-volume manufacturing.
Technical Skills and Relevant Technologies
- Advanced analytics: Python (pandas, numpy, scipy), R, SQL, Jupyter, RStudio.
- Machine learning / CV: OpenCV, TensorFlow or PyTorch for activity recognition and pose estimation.
- Data integration and ETL: Airflow/Prefect, pandas, dbt, REST APIs, CSV/Parquet handling.
- Visualization & reporting: Tableau, Power BI, Looker, or equivalent dashboarding tools.
- Sensors & hardware: IMUs, RFID/UWB, wearable devices, ingressing PLC/SCADA/OPC-UA logs.
- Cloud & infrastructure: AWS/GCP/Azure fundamentals, Docker, basic Kubernetes experience preferred.
- Measurement standards: MTM/PMTS, stopwatch protocols, inter-rater reliability frameworks, statistical sampling techniques.
Soft Skills and Cultural Fit
- Technical leadership: track record of leading measurement programs, authoring ADRs, and guiding technical decisions with evidence.
- Clear communicator: ability to present statistical findings and operational recommendations to executives and frontline teams.
- Coaching mindset: experience mentoring analysts and building training curricula for consistent data quality.
- Pragmatic problem-solver: comfortable balancing methodological rigor with operational constraints and delivering scalable solutions.
- Collaborative operator: demonstrated ability to partner with engineering, product, operations, EHS, and HR to implement sustainable change.
Benefits and Perks
Salary range: [$SALARY_RANGE]
We offer a comprehensive benefits package including:
- Medical, dental, and vision insurance
- 401(k) or local retirement plan with company match
- Generous paid time off and paid parental leave
- Annual professional development stipend and certification support
- Flexible work arrangements where operationally feasible and paid travel for onsite studies
- Equity or long-term incentive plans (where applicable)
Equal Opportunity Statement
[$COMPANY_NAME] is an equal opportunity employer. We are committed to building an inclusive workforce and welcome applicants from all backgrounds. All employment decisions are made without regard to race, color, religion, sex, gender identity or expression, sexual orientation, national origin, disability, protected veteran status, or any other status protected by applicable law. Reasonable accommodations are available upon request for candidates taking part in all aspects of the selection process.
Location
This role is primarily onsite in [$COMPANY_LOCATION] to support field studies and shop-floor data collection. Some remote work may be permitted for analysis, reporting, and cross-functional collaboration; successful candidates should expect regular on-site presence aligned with project schedules.
Application Instructions
We encourage applicants who may not meet every listed qualification to apply. Please submit your resume and a brief cover letter describing a representative time study or measurement project you led, the methods and tools used, and the measurable operational impact achieved.