Manage client risk and ensure high margins through positive expected value decisions. Oversee depth chart accuracy and analyze betting trends to execute quantifiable trading actions.
Swish Analytics
21 Remote Job Openings at Swish Analytics
Design, build, and optimize low-latency core API services and backend applications. Collaborate cross-functionally to develop internal platforms and SDKs while influencing the technical direction of distributed services.
Act as the primary point of contact for B2B clients to ensure product adoption and maximize value through technical support and relationship management. Collaborate with internal product and engineering teams to resolve client issues and relay feedback for product improvement.
Architect and build core real-time trading engines and multi-venue execution systems for sports betting. Develop position tracking, risk management systems, and low-latency data pipelines to support fair value models.
The analyst will work with data scientists and engineers to diagnose data pipeline integrity issues and detect inaccuracies in on-field data. They will also define validation tests, research roster statuses, and support feature development for predictive models.
You will design and develop a next-generation data analytics platform while standardizing development processes. You will also collaborate with cross-functional teams to drive technical design and ensure smooth deployment cycles.
The Senior Data Platform Engineer will manage and optimize enterprise database architecture, including monitoring, performance tuning, and disaster recovery. They will also develop scalable data infrastructure and automation tools to support real-time sports analytics products.
Monitor live sports markets and refine pricing models using statistical analysis and market signals. Manage real-time trading risk and collaborate with engineering teams to improve pricing infrastructure and execution tools.
The Senior Database Engineer will directly impact the data infrastructure for core consumer and enterprise data offerings, focusing on building new products with modern technologies. Responsibilities include developing performance testing strategies, query optimization, managing database environments from production to big data analytics, and ensuring 24/7 monitoring and incident response.
The role involves developing high-performance, low-latency products using sophisticated and readable Rust code for complex data science infrastructure. Responsibilities also include designing core backend components, building internal/external tools for the live trading platform, and debugging data pipeline dependencies.
The Trading Analyst will manage client risk to ensure maximum margins through positive Expected Value decisions and oversee depth chart accuracy with time-sensitive adjustments pre-match and in-play. Responsibilities also include strategically researching verified news sources to uncover market-impacting information and independently analyzing betting trends scientifically to drive quantifiable trading actions.
The role involves ideating, developing, and improving machine learning and statistical models that power the company's core sports betting products. Responsibilities include developing contextualized feature sets, contributing to all stages of model deployment, and analyzing results to improve performance.
The role involves supporting production systems, triaging issues during live sporting events, and architecting low-latency, real-time analytics systems from raw data collection to endpoint production. Responsibilities also include building new sports betting data products and integrating complex real-time datasets into consumer and enterprise offerings.
The role involves ideating, developing, and improving machine learning and statistical models that drive core algorithms for state-of-the-art sports betting products. This includes developing contextualized feature sets, contributing to all stages of model development, and rigorously analyzing results to improve performance.
The engineer will design, prototype, implement, evaluate, and optimize systems to generate highly accurate, low-latency sports datasets and predictions. They will also build, test, deploy, and maintain production systems while optimizing the data scientist's modeling workflow.
The Senior Quantitative Researcher will own end-to-end research and production pipelines for trading strategies, leading alpha research initiatives using advanced statistical and machine learning techniques. Responsibilities also include building risk monitoring systems, developing models for position sizing and portfolio optimization, and guiding junior researchers.
Senior Quantitative Researcher - Market Microstructure
Swish Analytics
·
·
3 months ago
Swish Analytics
The Senior Quantitative Researcher will own end-to-end research and production pipelines for trading strategies, leading alpha research initiatives using advanced statistical and machine learning techniques. Core duties include analyzing high-frequency tick data, building Monte Carlo simulations, developing and backtesting quantitative strategies, and mentoring junior researchers.
This is an open application inviting talented individuals passionate about sports, data, and building great products to connect with the growing company. The team will keep submitted information on file for future opportunities as they arise across various functions.
The role involves ideating, developing, and improving machine learning and statistical models that drive core algorithms for state-of-the-art sports betting products. Responsibilities also include contributing to all stages of model development, from proof-of-concepts to deployment, and constantly improving performance through rigorous experimentation.
The analyst will manage client risk to ensure maximum margins on products through positive expected value decisions and oversee depth chart accuracy with time-sensitive adjustments in both pre-match and in-play settings. Duties also include strategically researching verified news sources to uncover market-impacting information and independently analyzing betting trends scientifically to drive quantifiable trading actions.
The role involves having a direct impact on the data infrastructure for core consumer and enterprise data offerings, focusing on building new products with modern technologies. Responsibilities include developing KPIs, SLAs, and strategies to improve database stability, alongside managing performance testing and query optimization.
