Data Scientist Semi Senior - Causal Inference #5

免费注册后解锁"你的匹配分 vs 高分画像"与个人技能缺口。

🚀 Join Our Remote Data Products Machine Learning Startup! 🚀 At Muttdata, we build innovative Data Products and Machine Learning solutions that help companies solve complex business challenges. As a fast-growing, remote-first startup, we're passionate about technology, collaboration, and continuous learning. We are looking for an analytical, curious, and business-minded Data Scientist Semi Senior 🐶🚀 to join one of our key engagements with a leading beverage company in Mexico. You will be the go-to person for measuring what really works in growth and marketing: designing experiments, estimating causal impact, and turning the results into decisions that drive customer acquisition, retention, and revenue. This role sits at the intersection of statistics, economics, and marketing. You will work closely with marketing, growth, and commercial stakeholders, as well as with Data Engineers and Analytics Engineers, to move beyond correlations and answer questions like "Did this campaign actually cause an increase in sales?" or "Which promotions and channels deserve more budget?". A strong analytical profile, methodological rigor, and the ability to communicate findings to non-technical audiences are essential. A background in Economics (or similar quantitative fields) is highly valued. 🚀 What We Do Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting. Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client. Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems. Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster. Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval. Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions. 🌟 Our Partnerships Amazon Web Services Astronomer Databricks 🌟 Our Values 📊 We are Data Nerds 🤗 We are Open Team Players 🚀 We Take Ownership 🌟 We Have a Positive Mindset 🔍 Curious about what we’re up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on! 🚀 Responsibilities 🤓 Design, run, and analyze A/B tests and multivariate experiments (sample size and power calculations, randomization, guardrail metrics, interpretation of results). Apply causal inference techniques (Difference-in-Differences, Synthetic Control, Propensity Score Matching, Instrumental Variables, Regression Discontinuity, uplift modeling) to estimate the impact of marketing campaigns, promotions, pricing, and loyalty initiatives when randomization is not possible. Measure and optimize marketing performance: incrementality, attribution, ROI/ROAS, customer lifetime value (CLV), and marketing mix modeling (MMM). Translate business questions from growth and marketing teams into well-defined analytical problems and experimental designs. Develop analyses, features, and models on Databricks (notebooks, Spark, Delta Lake), collaborating with Data Engineers and Analytics Engineers on data pipelines and analytical datasets. Build predictive and segmentation models (churn, propensity, customer segmentation) that support targeting and personalization strategies. Required Skills 3+ years of experience in Data Science, Applied Statistics, Econometrics, or similar analytical roles. Hands-on experience with Databricks (notebooks, Spark/PySpark, Delta Lake) – required. Solid, hands-on experience designing and analyzing A/B tests and online/offline experiments. Strong knowledge of causal inference methods and their assumptions, limitations, and practical application (DiD, Synthetic Control, Matching, IV, uplift, etc.). Strong foundations in statistics and econometrics (hypothesis testin

🚀 加入我们的远程数据产品机器学习初创公司！🚀 在Muttdata，我们构建创新的数据产品和机器学习解决方案，帮助企业解决复杂的业务挑战。作为一家快速成长的远程优先初创公司，我们对技术、协作和持续学习充满热情。我们正在寻找一位善于分析、充满好奇心且具备商业思维的数据科学家（半高级）🐶🚀，加入我们与墨西哥一家领先饮料公司的关键合作项目。你将成为衡量增长和营销中真正有效之处的核心人物：设计实验、估计因果影响，并将结果转化为推动客户获取、留存和收入的决策。这一角色处于统计学、经济学和营销的交叉点。你将与营销、增长和商业利益相关者，以及数据工程师和分析工程师紧密合作，超越相关性，回答诸如“这次活动是否真的导致了销售额增长？”或“哪些促销和渠道值得更多预算？”等问题。强大的分析能力、方法论严谨性，以及向非技术受众传达发现的能力至关重要。经济学（或类似定量领域）背景将备受重视。🚀 我们做什么 依托我们的专业知识，我们构建用于需求规划和预算预测的现代机器学习系统。我们开发可扩展的数据基础设施，增强高层决策能力，并为每位客户量身定制。我们提供全面的数据工程和定制AI解决方案，优化基于云的系统。利用生成式AI，我们帮助电子商务平台和零售商更快地创建更高质量的广告。我们构建深度学习模型，增强各行业的视觉识别和自动化能力，改善产品分类、质量控制和信息检索。我们开发推荐模型，在电子商务、流媒体和数字平台中个性化用户体验，推动参与度和转化率。🌟 我们的合作伙伴 Amazon Web Services Astronomer Databricks 🌟 我们的价值观 📊 我们是数据极客 🤗 我们是开放型团队合作者 🚀 我们勇于担当 🌟 我们拥有积极心态 🔍 好奇我们在做什么？查看我们的案例研究，并深入阅读我们的博客文章，了解更多关于我们的文化以及我们正在进行的激动人心的项目！🚀 职责 🤓 设计、运行和分析A/B测试和多变量实验（样本量和功效计算、随机化、护栏指标、结果解读）。应用因果推断技术（双重差分、合成控制、倾向得分匹配、工具变量、回归断点、提升建模）在无法随机化时估计营销活动、促销、定价和忠诚度计划的影响。衡量和优化营销绩效：增量性、归因、ROI/ROAS、客户终身价值（CLV）和营销组合建模（MMM）。将增长和营销团队的业务问题转化为明确定义的分析问题和实验设计。在Databricks（notebooks、Spark、Delta Lake）上开发分析、特征和模型，与数据工程师和分析工程师协作处理数据管道和分析数据集。构建预测和细分模型（流失、倾向、客户细分），支持定向和个性化策略。所需技能 3年以上数据科学、应用统计学、计量经济学或类似分析岗位的经验。具备Databricks（notebooks、Spark/PySpark、Delta Lake）的实操经验——必需。在设计和分析A/B测试及线上/线下实验方面具有扎实的实操经验。深入了解因果推断方法及其假设、局限性和实际应用（DiD、合成控制、匹配、IV、提升等）。在统计学和计量经济学方面具有扎实基础（假设检验

⚑ 岗位信息收录自公开招聘页（Himalayas），以雇主官网为准