Data Scientist
2 weeks ago
Things to know before applying:
you must have your own work equipment
you are able to work remotely
you can work full-time for this role
experience working with clients/companies outside PH is an advantage
Key Responsibilities:
Design, develop, and maintain scalable, automated, user-friendly systems that will support our analytical and business needs.
Use SQL and Snowflake to create complex data models, perform efficient data extraction, transformation, and loading (ETL) processes, and ensure high data quality and integrity.
Build and manage API integrations to support data exchange and workflow between internal systems and external services, ideally using .NET framework.
Develop custom data models and algorithms to apply to data sets, with a focus on improving performance, scalability, and accuracy of internal data processing.
Actively promotes our mission of impacting as many lives as possible through the delivery of fun and affordable fitness.
Actively displays and cultivates our House of Values.
Accountable for the end-to-end management of data systems and processes, encompassing the design, development, and maintenance of scalable, automated solutions to support data analysis and business decision-making.
Accountable for leading the integration and effective utilisation of data-related technologies, including SQL, Snowflake, and API integrations (preferably with .NET), to ensure robust data quality and seamless data exchange between various platforms.
Accountable for leveraging statistical analysis and machine learning to create sophisticated data models and algorithms, delivering insights that inform strategic business initiatives and maintaining a pulse on industry advancements to keep the organization at the forefront of data science applications.
Stay up to date with industry trends, technologies, and advancements in data science, machine learning, and software development to continually enhance our capabilities.
Qualifications:
Bachelor's or master's degree in computer science, Data Science, Mathematics, Statistics, or a related field.
Strong proficiency in SQL and experience with Snowflake data warehousing, including a deep understanding of data modeling, performance tuning, and warehouse design.
Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
Experience with statistical computer languages (R, Python, etc.) to manipulate data and draw insights from large data sets.
Advanced analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Excellent written and verbal communication skills for coordinating across teams and explaining complex technical concepts to non-technical stakeholders.
A drive to learn and master new technologies and techniques.
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