Job Responsibilities:
- Lead a small team of Data Scientists.
- Lead the clients’ discussion for design, development and testing of enhancements spanning multiple areas ranging from moderate to high complexity.
- Develop and manage the end-to-end lifecycle of analytics projects from requirement, data scoping, modelling to production (model deployment and monitoring).
- Carry out preprocessing of structured and unstructured data.
- Enhance data collection procedures to include all relevant information for developing analytic systems.
- Work with product owners and engineering teams throughout the product development lifecycle from concept, design, prototyping, acceptance testing, data curation, delivery, operationalisation, industry proliferation, to product end-of-life.
- Propose, implement, and validate algorithms, ensuring functional and non-functional requirements such as transparency, fairness, scalability, security, integration complexity and operational costs.
- Lead small-scale projects on his/her own with supervision.
- Proactively lead/contribute and support projects in his/her respective area of expertise.
Job Requirements:
- BS in Computer Science, Mathematics, Statistics, Data Science or related discipline is required. PhD and MS degrees related to Machine Learning and other AI disciplines are preferred.
- Minimum 5 - 7 years’ professional experience in data analytics fields/Machine Learning.
- Strong knowledge in the areas of data science, programming languages (Python, SQL), machine learning and modelling technologies, statistical analysis, management, and strategic techniques.
- Experience in data processing, feature selection, hyper-parameter optimization, model validation and visualization.
- Prior experience in text analytics and network analytics is desirable.
- Experience in Data Analysis/numerical computing/classical ML tools like Pandas, NumPy/SciPy, Scikit-Learn, or XGBoost.
- Able to develop SQL queries and working with data models.
- Experience in production software engineering routines such as test-driven development, code versioning with Git, conducting code reviews, and CI/CD.
- Familiar with object-oriented programming concepts and their application to data science pipelines.
- Deep and eager interest in emerging technologies and the ability to leverage the technologies into solutions to meet our strategic and operational client needs.
- Some hands-on experience with AWS, or similar public cloud environment.
- Able to work in a fast-paced, rapidly growing company and handle a wide variety of challenges, deadlines, and a diverse array of contacts.
- Excellent problem-solving and analytical skills, as well as the ability to communicate complex findings to non-technical stakeholders.
