Senior Data Scientist at Schneider National, Inc.
Allouez, WI 54301
About the Job
Location: Green Bay, WI
Shift: 1st Shift
Work model: Hybrid
Schedule: FULLTIME; Mon-Fri 1st Shift
Job overview:
Schneider is seeking a Senior Data Scientist in Green Bay WI to design and implement analytic models that deliver actionable business insights and decision support. The Senior Data Scientist will be responsible for data identification, data preparation, model selection and model creation, as well as preparing reports of findings and presenting them to company executives.
Responsibilities:
Skills and qualifications:
Pay and benefits:
Shift: 1st Shift
Work model: Hybrid
Schedule: FULLTIME; Mon-Fri 1st Shift
Job overview:
Schneider is seeking a Senior Data Scientist in Green Bay WI to design and implement analytic models that deliver actionable business insights and decision support. The Senior Data Scientist will be responsible for data identification, data preparation, model selection and model creation, as well as preparing reports of findings and presenting them to company executives.
Responsibilities:
- Apply the appropriate methods, models and analysis based on clients' business needs.
- Gather and integrate business information and data into appropriate models and tools to support the development of solutions.
- Communicate technical engineering solutions and results into appropriate business language for clear client understanding.
- Prepare proposals, statements of work, project logs and presentations.
- Collaborate with other associates on projects.
- Document project assumptions, approaches and results, including net savings and profits.
Skills and qualifications:
- Master degree or PhD in data science, computer science, information systems, mathematics or related field.
- Four to six years of data science experience.
- Able to build effective business relationships with customers and other associates.
- Knowledge of statistical modeling and solution techniques.
- Able to understand the uses and limitations of statistical methodologies such as time-series forecasting, logistic regression, random forests, k-means clustering, Bayesian methods and machine learning.
- Able to learn and utilize statistical programming languages and tools such as R, SAS, Python SQL, SPSS and Tableau.
- Able to effectively communicate technical information and concepts to non-technical audiences.
Pay and benefits:
- Medical, dental and vision insurance.
- Company paid life insurance.
- 401(k) savings plan with company match.
- Paid time off and paid holidays.
- Results-based incentive pay program where you can earn above and beyond your base pay.
- Tuition reimbursement.
- See full list of .
