DNSE

Tóm tắt công việc

We are looking for a Data Scientist who will directly participate in our product development as we aim to build innovative product features with Deep learning/Machine Learning & Artificial Intelligence. The goal is to use DL/ML & AI to revolutionize the way Vietnamese people trade and invest stocks and securities and bring the maximum values and opportunities for our customers. The Data Scientist will also lead projects to support our product, sales, leadership and marketing teams with insights gained from analyzing company data. 

The ideal candidate should be adept building deep learning/machine learning models, especially predictive models from large data sets based on trends / human behaviors, for our intended product. He/she must have strong experiences with different techniques to test and optimize DL/ML models. He/she should have experiences with Machine learning operations (MLOps) including model deployment and model monitoring. He/she should have experiences with Natural language processing. They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes. 

Expertise in Finance, Banking and Stock Investing is a huge plus, but not required. Must be willing to learn Stock investing domain.

Responsibilities for Data Scientist

• Work directly with our Investment Advisory department to brainstorm and build ML models for innovative products
• Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
• Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
• Develop company A/B testing framework and test model quality.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Develop processes and tools to monitor and analyze model performance and data accuracy 

• Fastest growing fintech startup with state-of-the-arts technology
• Top notch engineering team
• Competitive salary with regular review and advancement
• Opportunity to take charge of your own works and directly contribute to company products
• Small, young and close-knit team. We move fast, work hard and play hard. 

• Strong problem solving skills with an emphasis on product development.
• Deep knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Deep knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques.

We’re looking for someone with years of experience manipulating data sets and building statistical models, has at least a Bachelor in Statistics, Mathematics, Computer Science or another quantitative field (a Master and/or PhD degree is preferred, but not required), and is familiar with the following software/tools:

• Coding knowledge and experience with several languages: Python, R, Java, Go, etc.
• Experience using deep learning frameworks (Pytorch, Tensorflow)
• Experience with Natural language processing models
• Experience with Machine learning operations (MLOps) including model deployment, model monitoring and model serving.
• Experience querying databases and using statistical computer languages: R, Python, SQL, etc.
• Experience with Hadoop ecosystem: HDFS, Spark, Kafka, etc.
• Experience visualizing/presenting data for stakeholders using: ggplot, Powerpoint, PowerBI, Metabase, etc. Periscope