Senior Data Scientist - Software

<Job Responsibilities>
- Work across the data value chain based on the project and client opportunity, with responsibilities ranging from performing deep-dive data analyses, developing predictive models and forecasting tools, building analytics dashboards, and developing end-to-end data strategies.
- Problem-solve, disaggregate issues, develop hypotheses and develop actionable recommendations from data and analysis.
- Take ownership of work delivery, assessing a problem and designing the approach, developing the data science solution, presenting the results to stakeholders, and where appropriate, preparing and facilitating workshops.
- Keep your skills up to date with the latest developments in data science and AI and contribute to thought leadership and knowledge share initiatives across the company.
- Coach and mentor team members as we grow.

<Necessary Skill / Experience >
・Education Background: Bachelor/ Master Degree in Quantitative field (e.g. Engineering, Mathematics, etc.)
・Language Skills: English - Business Level
・Experiences & Skills required:
- More than 4 years of professional experience in data sciences.
- Ability to think analytically, decompose problem sets, and develop hypotheses and recommendations.
- Solid understanding of the strategic impact of Data and Insights on business strategy and operations.
- Strong technical skills in data analysis, statistics, and programming.
- Ability to speak the language of statistics, finance, and economics to technical and non-technical audiences.
- Pragmatic approach to data and comfortable working with complexity and ambiguity.
- Problem solving skills.
- Positive and empathetic team player with an inclusive collaborative approach
- Strong working knowledge of SQL, Python, and/or R; Tableau and Power BI
- Strong test-and-learn mindset, with a solid understanding of A/B testing.

<Preferable Skills>
- Experience in Insurance or Healthcare would be advantageous.
- Experience in mobile app monetization, and customer and marketing analytics (eg, segmentation, churn modeling, recommendation engines) would be also advantageous.
- Experience with augmenting and fine-tuning LLMs would be advantageous.

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