Data Science - Business System Analyst
Description
A Fortune 500 Global Insurance company is seeking a Business System Analyst with Data Scientist & Analytics background.
Responsibilities
- Collaborate with business stakeholders to gather requirements, understand business context, and derive data-driven solutions
- Lead and oversee data analytics initiatives, including planning, executing, and delivering high-quality analytical solutions
- Work in close collaboration with the data platform team and other IT teams, identifying dependencies and resolving blockers to ensure smooth development processes
- Utilize CI/CD, MLOps, Azure or similar cloud platforms, and DevOps to streamline development and deployment processes
- Utilize hands-on skills with SQL, Python, Pandas, PySpark, AzureML, and PowerBI to develop and implement data models and analytics
- Prepare detailed documentation for analytics and ML initiatives, including project deliverables
- Communicate effectively with team members and leadership through presentations on analytics and machine learning requirements, progress, and outcomes
- Work with the Application Development team to implement data strategies, build data flows
【Company Details】
A U.S.-headquartered insurance company with offices in major cities around the world and a 40+ year history in Japan. The company focuses on creating a diverse environment, including the promotion of women, and supports their career development in Japan and abroad.
【Working Hours】
9:00 - 18:00(Mon - Fri)
*Hybrid (2 days Work from Home per week)
【Holidays】
Saturday, Sunday, and National Holidays, Year-end and New Year Holidays, Paid Holidays, and Other Special Holidays
【Services / Benefits】
Social insurance, Transportation Fee, No smoking indoors allowed (Designated smoking area), etc.
Required Skills
- Experience in advanced analytics roles within companies, delivering successful business outcomes
- Proven track record of success in advanced analytics roles, with strong leadership skills
- Proficiency in quantitative methods and business analytics, with strong problem-solving skills
- Ability to build and apply data models using machine learning techniques such as classification, regression, clustering, time-series analysis, and dimensionality reduction
- Competent in programming with tools like Python and SQL
- Strong understanding of data visualization tools, especially PowerBI
- Experience with CI/CD, MLOps, and cloud platforms like Azure for deploying analytics and ML solutions
- Hands-on experience with data analytics tools and libraries such as Pandas, PySpark, and AzureML