DESCRIPTION

Happy Global is a fast-paced, dynamic, pioneering vape distributor based in the United States. Our COE (Center for Excellence) team is searching for an insightful, results-oriented Data Science Manager who can consistently exceed expectations, who can thrive in a challenging workplace, and who can actively contribute to our talented team.

This position will coordinate between different teams within the company: Sales, Area Center, Product Center, Data Center, Marketing, Warehouses, Purchasing, Logistics, Finance, etc. Candidates will serve as first point of contact for communications with different teams to receive demands and requests. Candidates will be required to anticipate and identify problems accurately in a usually intense environment and provide reasonable problem-solving advice to the leadership. Candidates will use data analysis skills and techniques to provide thorough analysis of the company’s everyday operations and draw conclusions about business trends based on such analysis. Candidates are expected to complete analytical reports to help the company’s decision-making progress.

This role will demonstrate high judgment and deep business experience across end-to-end business cycles. They will bring proven ability to identify and recommend data-driven solutions, navigating through complex issues across multiple geographies. This role is highly strategic and will interact with all levels across a broad range of teams and leaders across Happy Global. This role will need to work with our business and product management partners to communicate the properties of their team’s analysis/modeling.

We are open to hiring candidates to work out of one of the following locations:

Dallas, TX, USA

Key Job Responsibilities

Ÿ Drive data fluency throughout the organization through the creation of standardized metrics, intuitive dashboards, and compelling business insights

Ÿ Design and implement analytic solutions and definitions that enable consistency & scalability with cross-functional teams

Ÿ Understand strategic priorities and business questions where analytic guidance is needed

Ÿ Apply advanced analytics and statistical modeling to support area center and sales teams

Ÿ Source, incorporate, and analyze alternative business data to drive innovation

Ÿ Balance multiple projects efficiently and achieve goals in a fast-paced, dynamic environment

Ÿ Collaborate effectively with the Sales, Area Center, Product Center, Data Center, Marketing, Warehouses, Purchasing, Logistics, and Finance teams, and senior management

Ÿ Use data to describe and visualize the current conditions and future trends of the company’s business operations

Ÿ Help business department monitor, identify and analyze problems during everyday operations and provide solutions on a timely basis

BASIC QUALIFICATIONS

· 3 years’ experience in fields such as business analytics, computer science, business intelligence, economics, mathematics, statistics or other quantitative area. Master’s level degree or higher preferred

· Superior analytical skills. Demonstrated ability to identify and solve ambiguous problems

· Demonstrated attention to detail and desire to roll up your sleeves

· Demonstrated ability to operate both strategically and tactically in a high-energy, fast-paced environment. High degree of organization and ability to manage multiple, competing priorities

· Excellent communication (verbal and written) and collaboration skills that enable you to earn trust at all levels

· 1 years of project management experiences

· Fluent in both Mandarin and English

· Proficiency in Office tools, especially Excel, at a level sufficient for business analysis

PREFERRED QUALIFICATIONS

· Proficiency in quantitative analysis tools like R, MATLAB, STATA, SPSS, SQL

· Proficiency in programming languages like Python

· PMP (Project Management Professional) Certification or project management experience for working on cross-functional projects

· Have experience of successfully navigating through fast-paced environment accompanied with ambiguity like startups