Data Analyst, Operations Specialist

As a Data Analyst, Operations Specialist at OSL, your responsibilities will encompass collecting and analyzing data from various sources, maintaining the supplier management system, automating sales revenue data processes, and developing performance dashboards. You will be instrumental in identifying operational inefficiencies and collaborating with cross-functional teams to ensure data accuracy while preparing reports for senior management.

To apply for the Data Analyst, Operations Specialist position at OSL, you should have a Bachelor’s degree in Business Administration, Operations Management, or a related field. Additionally, a minimum of 3 years of experience in an operations role is expected, along with strong analytical and problem-solving skills, proficiency in Excel, Python, SQL, and familiarity with business intelligence tools like Power BI or Tableau.

Important skills for a Data Analyst, Operations Specialist at OSL include strong analytical and problem-solving abilities, attention to detail, and proficiency in data analysis tools such as SQL and Excel. Additionally, effective communication skills in English, Cantonese, and Mandarin are critical, along with strong organizational skills and the ability to manage multiple priorities under pressure.

While not mandatory, prior experience in procurement and vendor management is considered a plus for the Data Analyst, Operations Specialist role at OSL. This experience can be beneficial, as it may enhance your ability to maintain the supplier management system and collaborate with the supply chain effectively.

The work environment for a Data Analyst, Operations Specialist at OSL is collaborative and fast-paced, given the dynamic nature of the digital asset industry. You'll have the opportunity to work both independently and as part of cross-functional teams, contributing to meaningful projects that support OSL's operational efficiency and strategic objectives.

In my work as a Data Analyst, I adopt a structured approach by first clearly defining the problem statement. I gather data from relevant sources, clean and organize it, and then utilize analytical tools to draw meaningful insights. I always ensure that my analysis aligns with business objectives and leads to actionable recommendations.

Absolutely! In my previous role, I analyzed the workflow of our supplier onboarding process. By identifying bottlenecks and implementing data-driven automation, we reduced onboarding time by 30%, significantly improving efficiency and supplier satisfaction.

I primarily use tools like Power BI and Tableau for data visualization and reporting. These platforms allow me to create interactive dashboards that present complex data in an easily digestible format, making it simpler for stakeholders to interpret insights and make informed decisions.

To ensure data accuracy, I implement a thorough verification process which includes cross-referencing data against multiple sources, validating assumptions, and conducting routine audits of the datasets. I also collaborate closely with data providers to address any discrepancies immediately.

When working under pressure, I prioritize my tasks based on urgency and impact. I break down larger projects into smaller, manageable tasks and use project management tools to keep track of progress. This ensures that I remain focused and meet deadlines without compromising quality.

I have extensive experience using SQL for data extraction and manipulation. In my previous positions, I frequently wrote complex queries to retrieve data from relational databases, which I then analyzed to generate insights that informed business strategy.

I handle conflicting requests by first gathering all the necessary information to understand the priorities and needs of each stakeholder. I then communicate openly to set realistic timelines, negotiate priorities where necessary, and ensure that everyone feels heard while highlighting the overall business objectives.

I have successfully implemented automation for various data processes using tools such as Python and Excel macros. By automating repetitive tasks, I’ve been able to free up significant time for more strategic analysis and improved data accuracy while significantly speeding up reporting cycles.

Yes, I regularly present data findings to non-technical stakeholders. I focus on simplifying complex data into key takeaways and using visual aids, such as charts and dashboards, to illustrate trends. I also encourage questions to ensure everyone understands the implications of the analysis on their work.

I am excited about the opportunity to work as a Data Analyst, Operations Specialist at OSL because I admire the company's innovative approach in the digital asset space. I believe that my analytical skills and operational experience align well with the company's goals, and I am eager to contribute to enhancing operational efficiency and leveraging data insights.