Title: Quality Data Analyst
Company Name: Bitopi Group
Vacancy: 01
Age: 23 to 40 years
Job Location: Manikganj
Salary: Negotiable
Experience:
Strong knowledge of Microsoft Excel (Pivot Table, Power Query, Advanced Formulas).
Knowledge of Power BI / Tableau (preferred).
Strong analytical and problem-solving skills.
Understanding of quality systems (AQL, DHU%, CAP, Root Cause Analysis).
Good communication skills.
Ability to work with cross-functional teams.
Experience in garments quality department.
Knowledge of Lean Manufacturing, Six Sigma, or Statistical Process Control (SPC).
Familiarity with digital inspection systems (e.g., Vista-Q or similar software).
Bitopi Group, a well-established manufacturing conglomerate with over 50 years of industry presence, is looking for a motivated Data Analyst – Quality to be based at their Manikganj facility. This is a great opportunity for a data-savvy professional from a statistics, engineering, or data science background who is eager to drive quality excellence in a dynamic manufacturing environment.
Job Responsibilities :
Data Collection & Management
Collect quality and production data from sewing, cutting, finishing, washing, and inspection sections.
Maintain accurate databases (AQL reports, inline/endline inspection data, DHU%, rejection reports, rework data, etc.).
Ensure data accuracy and integrity / Data Analysis & Reporting
Analyze defect trends, root causes, and process variations.
Monitor KPIs such as DHU%, RFT%, productivity, rejection rate, alteration rate, and efficiency.
Prepare daily, weekly, and monthly quality performance reports.
Develop dashboards and visual reports using Excel, Power BI, or similar tools.
Process Improvement & Identify improvement opportunities based on data analysis.
Support 5M analysis (Man, Machine, Method, Material, Measurement) for defect reduction.
Work closely with production, IE, and QA teams to implement corrective actions.
Audit & Compliance Support / Prepare data analysis for internal and external audits.
Support CAP (Corrective Action Plan) tracking and follow-up.
Predict quality risks based on historical trends.
Provide data-driven recommendations to management to improve output and reduce cost.
Service Benefits, Leave encashment & other benefits as per existing policy of the Company.