Data Science Engineer Apply now PRIMARY RESPONSIBILITIES * Create and maintain optimal data pipeline architecture, * Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability. * Experience/knowledge of employing statistical, data science and machine learning algorithms on real-world problems. * Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs * Work with product team, data science team and data engineer team to analyze product features, track user behaviors to drive feature enhancement or new feature development. * Identify and develop data collection strategies to support reporting on key performance indicators that directly measure online campaigns, website and conversion funnel performance * Designing and implementing automated reporting solutions across multiple teams and stakeholders. Translate the reports into business values and provide suggestions to drive effective business decisions. * Work with data engineer team on daily data quality monitoring and data validation. Create documentation and reports on data quality and data validation) * Supporting cross-functional teams on the day-to-day reporting/ visualization/ data analysis execution of different implementations. QUALIFICATIONS * Master's degree in Machine Learning, Data Science, Computer Science, Mathematics, Statistics, or related engineering field or a bachelor's degree with a significant amount of relevant work experience. * Retrieving and analyzing data using SQL/Python from SQL or NoSQL database such as SSMS, Postgres, MongoDB, Cassandra, etc. * Hands-on knowledge of data modelling tools, data mapping tools, and data profiling tools. * Experience with and theoretical understanding of algorithms for supervised and unsupervised modeling such as classification, regression, clustering, recommendation engine and anomaly detection * Experience in Python programming and familiarity with python libraries such as numpy, pandas, scikit-learn etc. * Expertise with statistical data analysis. (e.g. linear models, multivariate analysis, stochastic models, sampling methods, A/B testing) * Experience in deploying machine learning products in production using docker is a plus. * Experience supporting and working with cross-functional teams in a dynamic environment. * Experience with object-oriented/object function scripting languages: Python preferable. * Strong in BI technologies: e.g. Microsoft Power BI (preferable), Tableau, Google Analytics. * Experience building and optimizing 'big data' data pipelines, architectures and data sets, Azure Cloud experience preferred.