X0PA is a people management startup that utilizes data analytics, machine learning, and proprietary algorithms to produce data-driven, evidenced-based solutions for HR industry.
As a Data Scientist in X0PA you will contribute to the development of innovative products, and you will make a significant impact in the HR industry.
The candidate should be comfortable in exploring large datasets, run statistical analyses, build predictive models, and clearly communicate the results to other team members and customers.
We are looking for candidates with experience in developing data science solutions.
MS or PhD in Data Science, Statistics, Operations Research or in a related field, or similar level qualification and experiences in applying data science techniques to business problems or Bachelor’s degree with at least 3 years of work experience in data science.
- Continuous improvement of existing AI/ML features of our current products
- Research and develop new AI/ML features to existing products
- Partner with potential clients to undertake proof-of-concepts where you understand their needs and identify opportunities to apply data science
- Frame the opportunities as data science problems, formulate hypotheses, and identify techniques for experimentation
- Conduct experiments, assess model performance, and present results to business stakeholders
- Facilitate deployment of finalized solutions to production environment
- Accountable for the delivery of data science projects that drive value for business
- Streamline and automate existing data science pipelines
- Able to work collaboratively with a team of data scientists and software engineers
- Strong knowledge of statistical and data science algorithms including ensemble modelling, decision trees, probability networks, association rules, clustering, regression, and neural networks
- Strong coding skills in SQL, Python and/or R. Knowledge of C/C++ is a plus
- Good understanding of Natural Language Processing/Text mining and relevant techniques such as topic modelling, embeddings, LDA, sentiment analysis and text classification
- Experience in using causal and statistical reasoning
- Experience in deploying machine learning models into production environment through APIs
- Experience in building data pipelines using Azure services and pipeline orchestration tools (Kubeflow/Airflow)
- Experience in MLOps is a plus
- Exposure to Big Data (Spark) is a plus
- Experience in optimizations (linear programming, integer programming, dynamic programming) is a plus
- Expertise in API and using API documentation to extract data will be a plus
- Knowledge of setting up and maintaining feature stores is a plus