
Quantitative Analyst 2 (Advanced Analytics)
Identify business opportunities and implement analytical products to enable the organization achieves KPI targets on Cost, Delivery, Quality, and Yield. Products include descriptive, diagnostic, predictive, or prescriptive solutions.
Quantitative Analyst 2
- Implementations of analytical solutions to enable the organization discover data insights for business performance improvements.
- Proactive identification of opportunities and recommendation of creative solutions for business problems through analytics.
- Development of predictive and prescriptive models to help the business analyze future trends and improve efficiency.
- Development of reporting solutions such as BI dashboards based on business requirements, opportunities, and available tools.
- Storytelling and presentation of solutions in ways that both technical and non-technical users can easily understand.
- Partnering with multiple stakeholders to identify key business issues to be solved and frame them into analytical problems and solutions.
- Discussion with key users and process owners to understand and gather requirements, finalize design, and perform testing.
- Working with EDS Technology Product Owner and Data Engineering teams to develop required data foundations trough Asurion’s Enterprise Data Platform (EDP).
- Participation in CCM (change control management) and risk management discussions to maintain accuracy of data foundations as single source of truth.
- Continuous learning of business processes, business systems, and data entities to be able to generate accurate data insights.
- Research and prototyping of ML and AI solutions based on latest industry trends.
Work Experiences:
- Minimum 5 years of experience as Quantitative Analyst, Data Scientist or equivalent functions/roles.
- Solid experience in developing Machine Learning models.
- 5 years of total experience using analytical tools such as Python (for data science), BI Tools, SQL, and related products.
- At least 1 year of experience in a manufacturing environment. Exposure in electronics manufacturing is an advantage.
Competencies:
- Statistical analysis and methods
- Machine Learning process and frameworks
- BI development using Power BI
- Working knowledge of latest AI solutions particularly Generative AI.
- Good knowledge of data visualization, balance scorecards, KPI, metrics, and business dashboards.
- Above average SQL knowledge and understanding of data modeling.
- Good understanding of cloud technologies.
- ERP system experience as a user, application support, or functional consultant is an advantage.
- Good technical writing and communication skills and able to prepare high quality documentation, charts, and graphs pertinent to work assignments.
- Knowledge of project management, Agile/Scrum, or DMAIC process is an advantage.
- Above average presentation and communication skills.
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