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Intern - Lean Enterprise at MAS Holdings

Mawathagama, North Western Province, Sri Lanka -

Full Time

Start Date

Immediate

Expiry Date

03 Jul, 26

Salary

0.0

Posted On

04 Apr, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data modeling, Process optimization, Forecasting, Decision-making techniques, Data analytics, Analytical mindset, Data visualization, Operational research, Project coordination, Project tracking

Industry

Apparel & Fashion

Description

Intern - Lean Enterprise MAS Casualline – Mawathagama The Bodywear Value Stream of MAS Holdings delivers end-to-end design, innovation and manufacturing solutions across lingerie, swimwear and next-to-skin categories. It brings together broad expertise in fit, comfort, performance and aesthetics to serve leading global brands on a scale. With design and innovation hubs in Sri Lanka, the USA, Canada and Hong Kong and manufacturing operations across Sri Lanka, Bangladesh, India, Vietnam, Indonesia and Kenya, Bodywear offers a diverse portfolio spanning bras, briefs, shapewear, sleepwear, performance bodywear and Olympic grade swimwear. The value stream portfolio includes Victoria’s Secret, Calvin Klein, Marks & Spencer, Triumph, Speedo and Aerie. Positioned as a global centre of excellence, the Bodywear Value Stream combines advanced product innovation, technology-led solutions and operational scale to meet evolving consumer expectations across intimate and swim categories. KEY RESPONSIBILITIES: * Ability to support planning, coordinating, and tracking of ongoing improvement or operational projects. * Exposure to basic OR concepts such as data modeling, process optimization, forecasting, and decision-making techniques. * Strong analytical mindset with the ability to collect, interpret, and visualize data to support business decisions. KNOWLEDGE AND SKILLS: * Degree in Physical Science, Business Management, or a related field * Exposure to Operational Research * Data Analytics skills

Responsibilities

The intern will support the planning, coordination, and tracking of operational improvement projects. They will also utilize data modeling and process optimization techniques to support business decision-making.