Data Scientist in Supply Chain Analytics for Ford Motor Company. Leveraging technology and analytics to redefine transportation and enhance customer experience.
Responsibilities
Acquire deep understanding of the business problems and translate them into appropriate mathematical representations.
Work with large, complex data sets using tools such as Python, SQL, Google Cloud Services, Hadoop, Alteryx.
Develop and deliver business solutions using skills such as data acquisition, data engineering, programming, and visualization.
Design intuitive visual interfaces for users to interact with the data using dashboard and programming software.
Develop and deliver analytic products using skills such as predictive modeling, statistical analysis, machine learning, algorithm design, and interface development.
Interpret modeling results and communicate them to technical and non-technical audiences, cross-functional teams and leadership.
Interact and work cross-functionally with a wide variety of teams.
Develop trust with stakeholders and peers by delivering results on time.
Ensure overall quality of the data & solutions throughout the analytic development process.
Work with business teams on change management.
Provide training and maintenance of implemented tools to business partners.
Collect feedback from business users and continuously improve analytic products.
Requirements
Bachelor’s degree or foreign equivalent in Statistics, Data Science, Computer Science, Quantum Engineering, Nuclear Engineering or related field and 4 years of experience in the job offered or related occupation.
4 years of experience with the following skill is required: Predictive modeling, ML/AI, advanced statistical analysis, data mining, NLP, A/B testing, or design of experiments.
2 years of experience with each of the following skills is required: Python, with at least three of the following visualization/dashboard tools: Angular, React, Tableau, PowerBI, Qliksense, Palantir, Dash, Flask, LAMP (Linux, Apache, MySQL and PHP).
Develop analytical models using statistical and machine learning techniques, including linear and logistic regression, generalized linear regression, time series forecasting, decision and regression trees, random forest, LASSO, text mining, and Natural Language Processing.
1 year of experience with each of the following skills is required: Using R or Python for statistical analysis, modeling formation, feature modulization, and performing pre/post hypothesis testing.
Using SQL for acquiring and transforming data.
Real-world data, data cleaning, data collection or other data wrangling challenges through R and Python, or Alteryx and GCP native query.
Benefits
Immediate medical, dental, and prescription drug coverage
Flexible family care, parental leave, new parent ramp-up programs, subsidized back-up child care and more
Vehicle discount program for employees and family members, and management leases
Tuition assistance
Established and active employee resource groups
Paid time off for individual and team community service
A generous schedule of paid holidays, including the week between Christmas and New Year's Day
Paid time off and the option to purchase additional vacation time.
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