Data Scientist at 280 Nicol St Dairy Queen

Bloomington, Minnesota, United States -

Full Time

Start Date

Immediate

Expiry Date

02 Jan, 26

Salary

129313.0

Posted On

04 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Statistical Modeling, Data Analysis, Predictive Modeling, SQL, Python, R, Data Mining, Analytical Skills, Communication Skills, Project Management, Attention to Detail, Relationship Building, Innovation, Initiative

Industry

Food and Beverage Services

Description

Company Description Since 1940, Dairy Queen® has been one of the world’s best known and loved brands. Based in Minneapolis, MN, International Dairy Queen Inc., (IDQ), is the parent company of American Dairy Queen Corporation. As a leading franchisor, there are more than 7,000 independently owned and operated restaurants in the U.S., Canada and more than 20 countries around the world. IDQ is a subsidiary of Berkshire Hathaway Inc. (Berkshire) which is led by Warren Buffett, the legendary investor and CEO of Berkshire. Here at IDQ, we create extraordinary Fan experiences every day and we do this through our commitment to hiring and retaining only the best in class talent. We firmly believe that our employees are the catalyst to the success of the company where their initiative, strategic thinking, and entrepreneurial spirit are recognized and rewarded. We're looking for motivated, passionate and dedicated individuals with an inherent need and ambition to go after bigger challenges. Job Description We have an exciting opportunity available for a Data Scientist based out of our corporate office in Bloomington, MN. The Data Scientist will use advanced analytics, statistical modeling, and machine learning to optimize supply chain processes such as demand & supply-side forecasting, inventory management, and logistics planning. They will analyze large datasets from various sources to uncover insights, reduce costs, improve efficiency, and enhance decision-making by developing predictive models, designing optimization solutions, and creating data-driven tools. Key accountabilities include: Build predictive models to forecast demand, inventory needs, and lead times. Use components of mathematics, statistics, computer science, and domain-specific knowledge to gather, make, and communicate principled conclusions from data. Execute full life cycle of projects through project planning, data collection, model prototyping and deployment, with responsibilities encompassing stakeholder management and communication to cross-functional partners. The US national base salary range for this position is $105,561, - $129,313. This position is also eligible for a bonus. The base salary range displayed reflects the targeted hiring range for positions across all US locations. Individual pay is determined by job-related skills, work location and relevant education or experience. Qualifications Education/Experience: B.A. or B.S. Degree in Mathematics, Statistics, Analytics or related field or equivalent work experience in lieu of a degree Must have a minimum of 3-5 years of ML/AI experience Experience in applying statistical techniques like time series forecasting, regression, clustering, PCA, etc. Experience in applying ML algorithms like LTSM, Prophet, XGBoost / LightGBM, SVM, etc. Experience building ML/AI models, deploying to production and scaling to an enterprise level · Proficient in SQL, Python, R or other analytics programming languages Skills: Understanding of database structure, data mining skills and the ability to extrapolate, interpret and organize data to aid in forming fact-based conclusions Proficient in Microsoft Office, including Excel, Word and PowerPoint Ability to anticipate how decisions can affect our customers, our franchisees, and our employees Demonstration of innovation and initiative – always looking at improving products and processes while also displaying a willingness to dive into the details and help wherever necessary Exceptional analytical skills – creative thinker who can quickly develop innovative ideas across a wide variety of business units Keen attention to detail in planning, organization and execution of tasks, while still seeing the big picture and understanding how all the pieces fit together and affect one another Relationship building skills with the ability to create mutually beneficial relationships and provide excellent customer service to both internal and external customers Excellent written and verbal communication skills, with the ability to present information and articulate analytical results to a variety of internal and external customers Additional Information Benefits Our benefit package supports the well-being of our employees and their families. Our comprehensive benefit package includes, medical, dental, 401K match, paid time off (including volunteer time as well as parental leave) and so much more! To learn more about our great benefit offerings, Click Here. Work Environment Most positions located out of our global headquarters in Bloomington, MN will work a hybrid work schedule where you will work 2 collaboration days a week. Additional in office time may be required to support team/project needs. Positions will be identified as “remote eligible” when consideration will be given to candidates outside of drivable distance to our Bloomington office. Inclusion & Belonging We are committed to creating a culture of inclusion and belonging for all who touch DQ. We believe in and commit to fostering a community where employees bring their authentic selves to work, and where we recruit, engage, and retain employees, franchise owners, and suppliers based on qualifications and merit. We strive to maintain an environment where everyone feels welcome. IDQ is an Equal Opportunity Employer, and we use E-Verify to confirm the identity and employment eligibility of all new team members. You must be authorized to work in the United States without the need for employer sponsorship.

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Responsibilities

The Data Scientist will use advanced analytics and machine learning to optimize supply chain processes. They will analyze large datasets to uncover insights and develop predictive models.