Senior Data Scientist

freeC's Client

• Work with data science team(s), which includes Data Scientists, ML Engineers, Data Engineers and Analysts to create / design, optimize, build, and implement robust, secure, and scalable, applied machine learning algorithms.
• Design and build data driven systems for sales forecasting, lapse predictions, risk control, fraud detection, recommendation, customer segmentation, dynamic pricing etc.
• Optimize/ fine-tune, Improve the scalability, design, and robustness of existing ML algorithms, and techniques.
• Work with backend engineers, software engineers / data engineers / data architects to architect data storage and processing pipelines.
• Build, validate, test, and deploy models and algorithms including developing infrastructure that can support training a verity of different backends
• Work with product managers/ project managers or with multiple business units to develop new product features based on insights from data.
• Partner/ collaborate with a larger data science team including Data Scientists, Data Engineers, and Analysts to optimize business performance through optimizing ML algorithms.
• Stay up to date in advanced ML / AI/DL research and, ideas and software

- Education:

• BSc/ MSc or PhD in STEM field (Computer Science, Mathematics, Physics, Electrical Engineering, Machine Learning, Artificial Intelligence, etc...), evidence of strong mathematical and programming background (i.e. probability , statistics, optimization algorithms, computational complexity)

- Experience:

• At least three years of hands-on experience or BSc (3 years+ for MS or Higher ) in Vietnam in designing, developing and implementing large scale robust ML algorithms in areas such as propensity modeling, credit scoring, fraud detection, user -behavior modeling,NLP, sales prediction, recommendation systems and computationally intensive processes (i.e.: large scale Optimization / Simulation).
• Hands-on experience in applying statistical techniques such as regression, classification, clustering, survival analysis and experimentation in industry.
• Hands-on experience working in an agile environment and using MLOps / DevOps.
• Hands-on experience in translating analytical insights to clear business recommendations.
• Hands-on experience in launching production-sized machine learning models at scale.
• Hands-on experience working with diverse software engineering teams and collaborating with data engineering, solution architects, data architects, cloud architects etc..
• Solid experience in working with business teams and translating algorithm/model results to actionable business experience.

-Personal skills:

• Deep expertise in ML theory/ techniques and algorithms, Python and its machine learning libraries and frame works such as scikit-learn, XGBoost, Pandas, TensorFlow, PyTorch, Keras, etc.
• Ability to quickly learn new skills and technologies and apply those skills to solve business problems. Strong problem-solving skills and a Data-driven mindset with an emphasis on product development.
• Proficient in using MS Azure and Data bricks services for end-to-end Machine Learning projects.
• Solid programming skills in Python, SQL, R/Java/ Scala / C/C++or C# and in computer science fundamentals (data structures/algorithms, OOP, design patterns, and software engineering methodologies).
• Comfortable in debugging unfamiliar codebase.
• Sound knowledge in database systems, data engineering and data management techniques. Specially working with cloud-based systems and writing / configuring data pipelines.
• Good written and verbal communication skills for coordinating across teams