Applied Scientist

Quick Facts

• Role: Applied Scientist (Causal Inference & AIML)

• Focus: Marketing effectiveness, counterfactual modeling, lifetime value estimation

Description

You will design, develop, and deploy scalable causal inference and AIML solutions to improve understanding of Services marketing effectiveness. You will define technical vision and an execution roadmap for AIML initiatives, delivering high-quality, scalable models for customer acquisition and engagement. You will also champion innovation and continuous learning while collaborating with partners across Business, Marketing, Product, Finance, and Engineering.

Responsibilities

• Engineer end-to-end scalable Causal Inference products to assess the health of marketing efforts

• Dive into large-scale data sources to identify opportunities for causal inference automation, predictive methods, and quantitative modeling

• Collaborate with product managers, data scientists, and other engineering teams to translate business requirements into technical specifications and increase internal adoption of causal inference approaches

• Stay abreast of the latest advancements in causal inference and AIML research and integrate new frameworks as appropriate

• Champion best practices in software engineering, MLOps, code quality, testing, documentation, and ensure compliance with data privacy and security

Requirements

• Master’s degree in Statistics, Economics, Mathematics, Machine Learning, Computer Science, Engineering, or a related technical field

• 3+ years of experience as an Applied Scientist, Machine Learning, or Data Scientist

• Familiarity with quasi-experimental causal inference techniques (diff-in-diff, synthetic control method, panel analysis, regression discontinuity design, interrupted time series, propensity score matching)

• Hands-on experience building Marketing Mix models and validating via Matched Market testing

• Solid understanding of AIML technologies, including Generative AI

• Proven track record delivering complex projects end-to-end

• Proficiency in Python, R, SQL, Java, or C++

• Experience with cloud platforms, Spark, Docker, and MLOps tools and best practices

• Excellent communication and collaboration skills with attention to detail

Benefits

• Work with large, privacy-focused datasets and develop novel approaches

• Deliver material customer and business value through cross-functional collaboration

• Be part of a culture emphasizing innovation, continuous learning, and collaborative problem-solving