Build scalable data products, cloud-native data pipelines, and modern data platforms that support thousands of stores and millions of customer interactions.
Responsibilities
Design, develop, and support scalable data pipelines and data integration solutions.
Build data engineering solutions using Python, SQL, PySpark, and modern cloud technologies.
Develop and maintain trusted data products that enable analytics, reporting, operational intelligence, and AI use cases.
Contribute to enterprise data platforms built on Databricks, Apache Spark, and Lakehouse architectures.
Implement data quality, monitoring, testing, and observability capabilities to improve data reliability.
Requirements
Bachelor's or Master's degree in Computer Science, Data Science, Computer Engineering, Software Engineering, Information Systems, Mathematics, Statistics, or a related technical field.
Nice to have: Hands-on experience through coursework, internships, research, personal projects, or open-source contributions.
Nice to have: Familiarity with cloud platforms such as Azure, AWS, or Google Cloud Platform.
Nice to have: Exposure to Databricks, Apache Spark, Delta Lake, Airflow, dbt, Snowflake, or related technologies.
Nice to have: Experience using Git and modern software development tools.
Design, build, and support a laboratory operations platform that connects day-to-day lab workflows with our Laboratory Information Management System (LIMS).
Compensation
United States Base Compensation: $114,000.00 - $142,000.00
Responsibilities
Design, develop, test, deploy, and maintain full-stack capabilities across user interfaces, services, APIs, integration middleware, and data layers.
Translate user requests and operational needs into intuitive workflows and user experiences.
Define data models and build secure, traceable APIs for exchanging core sample, workflow, status, and metadata between the platform and the LIMS.
Contribute to architecture decisions and optimize application performance, scalability, reliability, security, observability, and supportability.
Extend the platform to integrate with laboratory instruments and automation systems.
Design and develop a next-generation scientific workflow platform that integrates sequencing data, synthetic biology expertise, public biological knowledge, and AI-enabled analytics.
Compensation
United States Base Compensation: $107,000.00 - $134,000.00
Responsibilities
Design and implement reusable algorithms, services, and workflow components to evaluate sequence designs, construct risks, manufacturability, and functional performance.
Build configurable analytical frameworks that integrate public scientific resources, proprietary algorithms, and standardized decision rules to support sequence and vector design workflows.
Develop customer-facing analytics, visualizations, APIs, and self-service tools that expose platform capabilities and turn biological data into actionable insights and recommendations.
Architect, develop, validate, and maintain scalable workflows for long-read, short-read, Sanger, and hybrid sequencing applications, including automated quality control, assembly, variant analysis, exception handling, and results delivery.
Apply AI and machine learning to automate workflow orchestration, data interpretation, quality assessment, troubleshooting, summarization, and continuous platform improvement.
Requirements
PhD
Master's
Nice to have: production-quality scientific software
The person will support market-making activities across stocks, forex, futures, and options, with the group’s current focus being binary options on ForecastEx exchange.
Compensation
Competitive salary, annual performance-based bonus, and stock grant awards
Responsibilities
Overseeing the activity and updates of the automated trading systems
Looking for anomalous activity
Tuning input parameters to control the activity
Support market-making activities across stocks, forex, futures, and options
Requirements
Bachelor’s degree in science, economics, or engineering
Take responsibility for stability of platform and control company standards, developing existing features, and implementing new functionalities across Europe supporting incident management.
Responsibilities
Take responsibility for stability of platform and control company standards
Develop existing features according to best practices
Implement new functionalities in 15+ countries across Europe
Lead and architect advanced analytics and machine learning solutions within the Microsoft cloud ecosystem to support strategic decisions in regulated healthcare environments.
Compensation
This role is compensated through a fixed annual salary. The expected salary range for this position is $170,000.00 – $180,000.00 annually, based on role scope, experience, and market considerations.
Responsibilities
Architect, design, and deploy advanced statistical, predictive, and machine learning solutions that support enterprise‑level decision‑making across healthcare, operations, finance, and customer/member domains.
Own end‑to‑end analytical solution lifecycle, including data discovery, feature engineering, modeling, validation, performance monitoring, retraining strategy, and retirement planning.
Serve as a technical authority on model explainability, fairness, robustness, and regulatory defensibility.
Design analytics solutions natively within the Microsoft cloud analytics stack, ensuring alignment to enterprise data architecture and governance standards.
Partner closely with executive stakeholders, data engineering leaders, and platform owners to translate complex business questions into high‑impact, production‑ready analytics.
Requirements
Master's degree in data science, statistics, mathematics, computer science, engineering, or related field
Principal‑level data scientist responsible for architecting, delivering, and governing enterprise‑grade advanced analytics and machine learning solutions in regulated healthcare environments.
Compensation
This role is compensated through a fixed annual salary. The expected salary range for this position is $170,000.00 – $180,000.00 annually, based on role scope, experience, and market considerations. This position is not eligible for bonus or incentive compensation.
Responsibilities
Architect, design, and deploy advanced statistical, predictive, and machine learning solutions that support enterprise‑level decision‑making across healthcare, operations, finance, and customer/member domains.
Own end‑to‑end analytical solution lifecycle, including data discovery, feature engineering, modeling, validation, performance monitoring, retraining strategy, and retirement planning.
Serve as a technical authority on model explainability, fairness, robustness, and regulatory defensibility.
Design analytics solutions natively within the Microsoft cloud analytics stack.
Partner closely with executive stakeholders, data engineering leaders, and platform owners to translate complex business questions into high‑impact, production‑ready analytics.
Requirements
Master's degree in data science, statistics, mathematics, computer science, engineering, or related field
The Information Risk function serves as the Bank’s Second Line of Defense (2LOD), independently assessing and monitoring information risks across the organization.
Responsibilities
Drive risk identification by proactively analyzing data from enterprise and technical management systems, security scanning tools, and identity management solutions to uncover and track risk trends.
Synthesize and communicate insights by aggregating complex data and generating detailed reports that inform key stakeholders and decision-making committees.
Deliver actionable recommendations for risk mitigation strategies, leveraging data-driven analysis to influence business outcomes.
Ensure accuracy and completeness of all risk management documentation and reports submitted to internal and external auditors and regulators, upholding the highest standards of integrity.
Collaborate strategically with business control offices and risk reporting functions to align and deliver timely information risk management reporting.
Requirements
Bachelor’s degree (preferred in Finance, Accounting, Business, or Analytics, Computer Science)
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