Data Scientist, Ops Research
1 week ago
**Background**:
The role will be in the interdisciplinary area of Operation Research, Optimization and Data Science. You will work on interesting multi-domain projects and diversified problems, related to resource plan & optimization, Machine Learning, AI, NLP, etc. You’ll be building optimization algorithms, modules or data pipelines responsive to the input of our Domain Expert, while having the freedom to explore new techniques to tackle the problems at hand.
- Contribute to IT projects in the Logistics industry for Antaes clients
- Identify business operation problems with clear objectives and propose feasible solutions and strategies.
- Build and improve solvers for planning/optimizing operations with constraints of assets, resources, and business rules.
- Build predictive models by supervised and supervised machine-learning models.
- Assist backend team to deploy optimization modules, solvers, or ML models into production.
- Collect, pre-process and clean structured and unstructured data not limited to text, webpages, databases, time series, geospatial data, etc.
- Collaborate with engineering and product development teams.
- Contribute to the promotion of Antaes services on top of assistance provided to clients.
**Job Requirements**:
- Bachelor’s degree or above in computer science, operations research, industrial engineering or related fields
- 1 to 3 years of experiences with **integer/mixed-integer/constraint programming, operations research libraries (e.g., Google Ortools)**
- Well experienced using **Python, data analytics packages, such as NumPy, SciPy, Pandas, Matplotlib, PyDash, etc.**
- Good experience with **ML algorithm and libraries (Scikit-Learn, etc.)**
- Able to program with **production-level codes **.
- Basic understanding of cloud web services and architect
- Self-motivated, strong learning capabilities and willing to work in various domains.
- Plus points if experienced in the following knowledge and tools**:
**(NLP, SpaCy, Scrapy, Flask, MongoDB, GeoPandas)
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