Job Closed
This listing is no longer active.
The World’s Leading Blockchain Ecosystem and Digital Asset Exchange
Data Scientist
Location
Singapore
Posted
97 days ago
Salary
0
Seniority
Senior
Job Description
Data Scientist
Binance
• Deploy and manage AI evaluation processes across our infrastructure to ensure reliable performance monitoring and continuous improvement of AI models. • Process and perform comprehensive data analysis to identify trends, inconsistencies, and opportunities for model enhancement. • Build and maintain scalable data pipelines that ingest raw data, perform transformations, and feed downstream systems. • Collaborate with cross-functional teams, including security, engineering, and product personnel, to embed security and compliance considerations into the development lifecycle. • Automate repetitive workflows and implement solutions to improve operational efficiency
Job Requirements
- Proficient in Python, with hands-on experience in making API calls using libraries such as requests and handling data formats like json. You will be expected to develop, test, and optimize scripts that interface with various data services and internal tools efficiently.
- Strong data processing skills in PySpark and SQL (Hive), enabling you to extract, transform, and load large data workloads in distributed environments to support timely and accurate data insights.
- Solid foundation in software development fundamentals, including version control (Git)
- Excellent problem-solving abilities and a logical mindset, allowing you to analyze challenges critically, identify root causes, and devise effective solutions.
- Eagerness to learn and strong communication skills, empowering you to engage effectively with team members, share knowledge, and take initiative in owning tasks from conception to completion, adapting quickly to new tools and technologies as needed.
- Experience with AI or evaluation-related projects, whether personal, academic, or professional, demonstrating familiarity with AI concepts, data labeling, model performance assessment, or related methodologies.
- Understanding of large language models (LLM) and issues such as hallucination, providing context for your work in AI evaluation and helping improve model reliability and trustworthiness.
- Hands-on experience with tools such as Label Studio (for data annotation), Airflow (for workflow orchestration)
Benefits
- Competitive salary and company benefits
- Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)
Related Guides
Related Categories
Related Job Pages
More Data Scientist Jobs
• Support customers’ and colleagues’ efforts to use our platform to deliver data integration, visualizations, models and recommendations that create meaningful impact • Work with customer teams to understand their goals and help develop data integration, modeling, and visualization plans to support decision making • Collaborate with customer and internal teams to develop, test, and validate simulation models, ensuring their accuracy and relevance for healthcare use cases • Provide guidance for proposals on feasibility of scope and how to ensure impact • Contribute to customer onboarding experiences and content, helping to ensure customers quickly achieve their first successes with the platform • Engage with customer users to provide informal support, tips, and troubleshooting • Collaborate with premium support customers by integrating data and creating models, simulations, or visualizations. Support recommendation development and action plans • Participate in reviews with customers to document and improve measurable impact • Provide feedback to Product and Sales teams to align offerings with customer needs • Follow advancements in data science, machine learning, and healthcare analytics
Principal Clinical Data Manager
SuperStaffComprehensive BPO, RPO, and Call Center Outsourcing Solutions for Growing Businesses
• Collaborate on the redesign and optimization of end-to-end data management processes including study start-up, maintenance, and close-out. • Evaluate and revise existing procedures to align with internal execution capabilities, ensuring operational efficiency, compliance, and scalability. • Provide strategic oversight of functional improvements across data management operations. • Oversee and contribute to the reengineering and execution of critical data management functions, including: • Study Set-Up • EDC Build and Maintenance • Data Cleaning and Query Management • Local Laboratory and External Data Handling • Clinical Coding • SAE Reconciliation • Blinding Procedures • Site Close-Out and Database Lock • Data Management Metrics and Clean Patient Tracker oversight • Ensure all data management activities comply with applicable regulatory requirements, CDISC standards, and internal quality standards. • Support audit readiness, inspection preparedness, and continuous quality improvement initiatives. • Identify and mitigate data-related risks proactively. • Represent the Data Management function within the clinical trial working group. • Ensure aligned expectations for all data-related deliverables, especially those supporting regulatory submissions and key milestone decisions. • Collaborate closely with Clinical Operations, Statistical Programming, Biostatistics, and other stakeholders to ensure timely database lock and delivery of high-quality data. • Provide influential leadership to ensure milestones and deliverables are met within timelines and budget. • Contribute to continuous improvement initiatives at the functional and organizational levels.
Principal Clinical Data Manager
SuperStaffComprehensive BPO, RPO, and Call Center Outsourcing Solutions for Growing Businesses
The Principal Clinical Data Manager (Sponsor-Dedicated) works fully embedded within a global pharmaceutical client, serving as the lead data management representative across assigned clinical studies. This role is responsible for overseeing end-to-end clinical data management processes, driving process reengineering initiatives, ensuring regulatory compliance, and delivering high-quality data in support of key decision points and regulatory submissions. The position combines strategic leadership with hands-on data management execution. Responsibilities & Duties: Process Reengineering & Oversight - Collaborate on the redesign and optimization of end-to-end data management processes including study start-up, maintenance, and close-out. - Evaluate and revise existing procedures to align with internal execution capabilities, ensuring operational efficiency, compliance, and scalability. - Provide strategic oversight of functional improvements across data management operations. Functional Area Ownership Oversee and contribute to the reengineering and execution of critical data management functions, including: - Study Set-Up - EDC Build and Maintenance - Data Cleaning and Query Management - Local Laboratory and External Data Handling - Clinical Coding - SAE Reconciliation - Blinding Procedures - Site Close-Out and Database Lock - Data Management Metrics and Clean Patient Tracker oversight Quality & Compliance - Ensure all data management activities comply with applicable regulatory requirements, CDISC standards, and internal quality standards. - Support audit readiness, inspection preparedness, and continuous quality improvement initiatives. - Identify and mitigate data-related risks proactively. Clinical Trial Leadership & Cross-Functional Collaboration - Represent the Data Management function within the clinical trial working group. - Ensure aligned expectations for all data-related deliverables, especially those supporting regulatory submissions and key milestone decisions. - Collaborate closely with Clinical Operations, Statistical Programming, Biostatistics, and other stakeholders to ensure timely database lock and delivery of high-quality data. - Provide influential leadership to ensure milestones and deliverables are met within timelines and budget. - Contribute to continuous improvement initiatives at the functional and organizational levels.
• Explore data to identify trends and evaluate performance • Design, implement, and optimize algorithms • Build and refine predictive models • Collaborate with product/business teams • Conduct and evaluate A/B tests • Create dashboards and communicate findings



