Salary: W2 only
Data Scientist (W2 only)
Must also have Python, R, Azure, AI/ML and data modeling experience!!!
No OPT/CPT candidates please!
Location: 100% Remote
Duration: 2+ years
Interview: MS Teams video interview then offer
Start Date: ASAP
W2 only - Visa transfers would be accepted
Manager seeking the following background:
As mentioned in the minimum requirements of the job description we provided for the role, we are looking for the following and more, but I have emphasized some of them below:
- Candidates with a Master’s degree with emphasis on coursework of a quantitative nature (e.g., Statistics, Computer Science, Engineering, Mathematics, Physics, Data Science, Industrial/Organizational Psychology and Econometrics, etc.) AND 4 years of experience working in a data analytical or computer programming function. The more experience, the better and this experience should be gained after finishing their studies. We find that experience gained during school is typically not as rich and robust as would be for a full-time employee. A PhD is preferred.
- Experience in quantitative analytics (e.g., data mining, regression analysis, hypothesis testing, A/B testing, machine learning modeling, including multivariate statistical analysis, natural language processing, unsupervised and supervised learning, deep learning, and predictive modeling, and model optimization in production.) I would also emphasize that it’s not about having applied any of these analytical techniques in school or on a work project, but it is about being able to determine what analyses and algorithms fit the problem they are being asked to solve. This judgment typically comes with experience and trial and error.
- Experience performing rigorous exploratory data analysis (EDA), hyperparameter tuning of models and putting models into production, especially in Microsoft Azure Cloud Platform using Databricks.
- Ability to coach junior team members is also expected and hence, the search for a candidate with more experience
- Ability to project manage and handle multiple requests at the same time with tight deadlines
- Adept at leveraging the Microsoft Azure platform and its AI and machine learning tools (e.g., Databricks, Data Factory, ML Studio) and business intelligence and visualization tools (e.g., SAP Business Objects, Microsoft Power BI)
- Intermediate- to advanced-level knowledge and skills in data modeling, data structure, and the application of complex SQL queries with data from multiple sources, including from a Big Data platform (e.g., Hadoop, AWS, Azure)
- Experience with SAP IS-U, CRM and Business Warehouse (BW) data would be a huge plus
The Data Scientist will be instrumental in supporting large business unit or enterprise-level analytics projects with broad responsibilities for translating business requirements into analytical constructs and providing analytical insights for effective decision making and communicating effectively to technical and non-technical stakeholders with strong domain expertise and business acumen. The role is also expected to mentor less-experienced team members to run analytical experiments in a methodical manner, evaluate alternative approaches and develop predictive models to forecast business performance metrics. Additionally, this role requires researching and recommending new technologies and best practices across industries to provide input to the organization’s analytics strategies and roadmap.
• Supports analytics projects and collaborates with cross-functional stakeholders to complete end-to-end analyses that includes business requirements, data gathering, analysis, scale-able solutions deliverables, including visualizations and presentations
• Conducts advanced statistical analysis to determine trends and significant data relationships, and proactively recommends areas of improvement
• Develops complex data sets and predictive models to support key decisions to improve safety, employee engagement, operational and financial efficiency, product quality, and customer satisfaction
• Prepares and delivers insightful presentations and actionable recommendations. Educates others on complex analytical findings in basic terms and with storytelling and data visualization
• Identifies and evaluates technologies and provides strategic input to advance the organization’s analytics capabilities
• Implements new, industry-leading statistical, mathematical, machine learning or other methodologies for modeling or analyses
• Responsible for discovering insights from Big Data to help shape or meet specific business needs and goals
• Utilizes business expertise to translate goals into data-based deliverables, such as predictive models, pattern detection analysis or optimization algorithms
• Champions self-service reporting capability and use of business intelligence and statistical tools to advance the analytical capabilities of the organization and use of data to make data-driven decisions
• Develops data and analytical processes based Continuous Improvement learnings and practices, including process maps, documentation, and job aids
Minimum Education and Experience Requirements:
• Master’s degree with emphasis on coursework of a quantitative nature (e.g., Statistics, Computer Science, Engineering, Mathematics, Physics, Data Science, Industrial/Organizational
Psychology and Econometrics, etc.) and 4 years of experience working in a data analytical or computer programming function
• Experience in quantitative analytics (e.g., data mining, regression analysis, hypothesis testing, A/B testing, machine learning modeling, including multivariate statistical analysis, natural language processing, unsupervised and supervised learning, deep learning, and predictive modeling, and model optimization in production)
• Intermediate- to advanced-level knowledge and skills in data modeling, data structure, and the application of complex SQL queries with data from multiple sources, including a Big Data platform (e.g., Hadoop, AWS, Azure)
• Proficient programming skills such as SQL, C/C++/C#, Java, R, Python, PHP, or SAS
• Have in-depth experience developing models in a Big Data cloud environment (Azure, AWS, GCP) and deploying and overseeing models running in production
• Adept at leveraging the Microsoft Azure platform and its AI and machine learning tools (Databricks, Data Factory, ML Studio, etc.)
• Intermediate-level skills and experience with data mining and statistical analysis using analytical packages / tools (e.g., R, SAS, SPSS, Stata, MATLAB, Minitab, etc.)
• Intermediate- to advanced-level skills and experience in articulating business questions, pulling data from relational databases (e.g., SAP Business Warehouse (BW), ORACLE, SQL SERVER) and using advanced excel and statistical tools (e.g., Minitab, Alteryx, Advanced Excel with VBA, R, SAS, SPSS, Stata, MATLAB, etc.), and determining the appropriate analytical approach to conduct in-depth analysis to support decision making
• Adept with multiple business intelligence tools and platforms (e.g., SAP Business Objects, Microsoft Power BI.)
• PhD degree in Data Science
• Intermediate-level or higher Continuous Improvement knowledge, skills, and certifications
• SAP ISU, CRM, and BW knowledge
• Strong written and oral communication skills
• Strong business acumen
Please send qualified resume to: [Click Here to Email Your Resumé]
Contact: [Click Here to Email Your Resumé]