Data Analyst

At Kotn, we’re reimagining the way our everyday items are made and purchased, beginning with your wardrobe, setting a new standard for social impact and traceability. Founded in February 2015, Kotn has been featured in over 80 publications such as New York Times, GQ, Vogue, Elle, and The Wall St. Journal. Kotn was founded in Toronto by three best friends, who were fed up with compromising on quality, design, sustainability, brand experience, and price.

Kotn is looking for a Data Analyst to Merchandising and Planning function. As an essential part of the Planning Team, the ideal candidate will be responsible for building data related to planning activities, e.g., demand forecasting, inventory management, receipts reconciliations, etc. to support effective decision-making and optimize our planning processes. The Data Analyst will work closely with cross-functional teams to gather required data to develop analytical models, the role will involve significant responsibilities related to data entry and data cleaning to ensure the integrity and accuracy of our planning data.

What you’ll be working on:

Data Collection and Cleaning (50%)

• Collaborate with stakeholders to understand business requirements and data needs related to planning processes.
• Collect, clean, and organize data from various sources, including internal databases, system, and different sources of sheets.
• Perform data entry tasks to input new data and update existing records.
• Support in developing the data needed to maintain analytical models and to support planning activities, such as demand forecasting, inventory optimization, sales planning, etc.
• Conduct data cleaning tasks to identify and rectify inconsistencies, errors, and missing values in planning data.

Reporting and Analysis (50%)

• Support in generating regular reports and dashboards to track key performance indicators (KPIs).
• Conduct ad-hoc analysis to support decision-making and address specific planning challenges.
• Customize reports to address specific questions or issues.
• Provide turnaround on reports for urgent business needs.

What you’ll bring:

Business understanding

Commercially and ethically oriented thought process to approach business problem solving with a focus on how to serve the customer.

Understanding of retail landscape and market knowledge to provide insights on trends and locations.

Organization

Excellent communication and interpersonal skills to collaborate with cross-functional teams.

Team skills

Ability to work collaboratively with dynamic teams cross functionally with varying backgrounds, cultural orientations, and different mind-sets.

Adaptability

Capability of adjusting to a fast-paced and dynamic environment which characterizes a start-up, learning new things quickly and figuring ways to do things more effectively and efficiently.

Affinity for data

Strong analytical and problem-solving skills with the ability to deal with data.

Additional Requirements:

• Bachelor’s degree in data science, Statistics, Mathematics, Economics, Computer Science, or a related field. Masters degree preferred.
• Proven experience (1-2 years) as a Data Analyst or similar role, preferably in a planning or supply chain environment.
• Proficiency in data manipulation and analysis using excel sheets.
• Strong analytical and problem-solving skills.
• Ability to work effectively in a fast-paced, collaborative environment with cross-functional teams.
• Attention to detail and a commitment to data accuracy and quality.

Working Hours:

• Standard Working Hours: Employees are expected to adhere to North American working hours, apart from Mondays when the working hours align with Egypt time.
• Working Days: The workweek spans from Monday to Friday, ensuring consistent availability and productivity throughout these weekdays.
• Remote Work Arrangement: Employees are granted the flexibility of working remotely for three days each week, while maintaining a presence at the office for two days. This arrangement promotes a balance between in-person collaboration and the convenience of remote work.