网球数据科学家
Tennis Data Scientist
公司简介
Swish Analytics 是一家体育分析、投注和幻想体育的初创公司,正在打造下一代预测体育分析数据产品。我们认为,赔率制定是一项根植于工程学、数学和体育投注专业知识的挑战,而不是直觉。我们寻找具有团队精神、对准确且可预测的实时数据有真诚热情的人才,他们能够在快节奏、富有创造力且不断发展的环境中执行任务,同时不牺牲技术卓越性。我们的挑战是独特的,因此我们希望你能在未知领域中感到舒适,并热衷于构建支持多种行业以及消费者/企业客户的系统。
职位描述
Swish Analytics 正在寻找一名网球数据科学家加入我们不断壮大的团队!数据科学是我们的核心业务,因此这个团队对开发 Swish 数据产品的核心组件拥有真正的所有权和影响力。该职位为远程办公,地点在美国。
职责:
- 构思、开发和改进驱动 Swish 核心算法的机器学习和统计模型,用于生成最先进的体育投注产品。
- 使用体育领域的专业知识构建上下文相关的特征集。
- 参与模型开发的所有阶段,从创建概念验证和测试,到与数据工程和产品团队合作部署新模型。
- 通过严格的离线和在线实验获得的见解,持续提升模型性能。
- 分析结果和输出,评估模型性能并识别模型弱点,以指导开发工作。
- 遵循软件工程最佳实践,并为共享代码库做出贡献。
- 记录建模工作并向利益相关者以及其他技术和非技术人员合作伙伴进行汇报。
- 要求:
- 数据分析、数据科学、计算机科学或相关技术领域的硕士学位
- 2 年以上在网球或体育投注领域开发生产规模模型的经验
- 精通概率论、机器学习、推断统计学、贝叶斯统计学、马尔可夫链蒙特卡洛方法
- 5 年以上在体育或体育投注领域开发和交付有效机器学习和/或统计模型以满足业务需求的经验
- 熟悉关系型 SQL 和 Python
- 有使用版本控制工具如 GitHub 的经验
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Company Description
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.
Job Description
Swish Analytics is looking for a Tennis Data Scientists to join our ever-growing team! Data Science is at the core of our business, so this team has true ownership and impact over developing core components of Swish's data products. This position is remote from the USA.
Duties:
- Ideate, develop and improve machine learning and statistical models that drive Swish’s core algorithms for producing state-of-the-art sports betting products.
- Develop contextualized feature sets using sports specific domain knowledge.
- Contribute to all stages of model development, from creating proof-of-concepts and beta testing, to partnering with data engineering and product teams to deploy new models.
- Strive to constantly improve model performance using insights from rigorous offline and online experimentation.
- Analyze results and outputs to assess model performance and identify model weaknesses for directing development efforts.
- Adhere to software engineering best practices and contribute to shared code repositories.
- Document modeling work and present to stakeholders and other technical and non-technical partners.
Requirements:
- Masters degree in Data Analytics, Data Science, Computer Science or related technical subject area
- Demonstrated experience developing models at production scale for Tennis or sports betting for 2+ years
- Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods
- 5+ years of demonstrated experience developing and delivering effective machine learning and/or statistical models to serve business needs in sports or sports betting
- Experience with relational SQL & Python
- Experience with source control tools such as GitHub and related CI/CD processes
- Experience working in AWS environments etc
- Proven track record of strong leadership skills. Has shown ability to partner with teams in solving complex problems by taking a broad perspective to identify innovative solutions
- Excellent communication skills to both technical and non-technical audiences
Base salary: $135,000 - $190,000
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of background and reference checks.
Originally posted on Himalayas