【Game changer, armed with data.】
You know all about our users, through data analysis. And because you do, you can identify issues and present insights to our Product Owners, spurring them into action. Working with your team, you play a key role in enhancing our business value. After all, you're the one who ignited the spark. And no spark, no fire.
【What a Data Scientist does in Titansoft】
．Apply statistical, ML/DL and generative AI techniques to build functions for user classification, fraud detection, sentiment analysis and other objectives.
．Conduct data analysis to support Product Owner and Business Leaders in business decisions and requirements.
．Develop and automate reports for analytical purposes.
．Collaborate with other Product Development teams to understand their business needs, formulate and complete end-to-end analysis that includes data gathering, analysis, ongoing scaled deliverables and presentations.
【What we are looking for in a Data Scientist】
1. Skills：
．Programming proficiency in Python (Scikit-learn, PyTorch), SQL (MsSql, BigQuery, MongoDB)
．Mathematics proficiency in statistics methodology, ML/DL algorithms, or generative AI theory
．Domain experience in CRM (GA, recommendation systems, LTV) or ChatBot (RAG, LLM) or anomaly detection will be preferred
．A/B and Multivariate testing management
．Data visualization skills (such as Tableau, Excel, etc)
．Ability to translate analysis results into business recommendations and insights
．Strong written, verbal communication and presentation skills for coordinating across teams and with stakeholders or non-technical audiences
．Strong problem solving skills
2. Experience：
．Have CRM (GA, recommendation system, LTV) or ChatBot (RAG, LLM) or anomaly detection relevant experience will be plus.
．Experience in analytic projects.
．Knowledge and experience in A/B testing and multivariate testing management.
．Experience in applying practical applications on production will be a plus.
【What makes a (Super!) Data Scientist in Titansoft AKA the "great to haves"】
．Deep interest and aptitude in data, metrics, analysis and trends, and applied knowledge of measurement, statistics and program evaluation
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