Why don't data scientists make good relationship counselors?
Because when a couple comes in saying "Every time I skip washing the dishes, my partner gets angry," the data scientist just shrugs and says, "Well, you've got a strong correlation there, but I'd need a randomized controlled trial to determine causation. Have you considered randomly assigning dish-washing duties across multiple households while controlling for confounding variables like who left the mess in the first place?"
We are seeking a talented Data Scientist - thankfully not for relationship counseling, but for one of our esteemed clients, a cutting-edge technology company that specializes in revolutionizing digital advertising measurement and brand safety through advanced AI and machine learning technologies. Our client provides sophisticated content analysis and contextual targeting solutions that go far beyond traditional keyword-based approaches, delivering granular insights across multiple media formats.
This role presents an exciting opportunity to address complex challenges in digital advertising analytics and measurement science. You'll be at the forefront of incrementality measurement—determining the genuine impact of advertising campaigns on business performance. The position involves working within highly regulated data environments including clean rooms and walled garden ecosystems, while handling complex, real-world datasets such as transaction-level purchase data extracted from retail receipts through scanning and OCR technologies.
We're seeking a creative, adaptable, and innovative data scientist who thrives on solving unconventional problems, developing cutting-edge methodologies, and exploring the boundaries of causal inference in controlled data environments and observational studies.
What You'll Do:
- Transform and organize complex retail transaction data, including receipt-level information and product catalog matching
- Operate effectively within SQL-constrained clean room environments for data analysis and processing
- Calculate incremental advertising impact on critical business metrics, including revenue and customer acquisition
- Implement both experimental (randomized controlled trials) and observational methodologies
- Deploy advanced causal inference techniques for longitudinal data analysis, including difference-in-differences, synthetic control methods, and their variations
- Apply causal machine learning approaches such as double machine learning and other innovative techniques
- Design and structure controlled experiments where feasible
- Create reliable causal inference frameworks for scenarios where traditional experimentation isn't possible
- Translate complex technical findings into accessible insights for business stakeholders
- Collaborate directly with clients to understand their business context, operations, and strategic objectives
- Explore and integrate novel data sources and analytical approaches to expand measurement capabilities
What We're Looking For:
- Exceptional analytical mindset with passion for data exploration and pattern recognition
- Expert-level SQL proficiency
- Advanced Python skills including data manipulation frameworks (Pandas, NumPy, etc.)
- Comprehensive Machine Learning knowledge with demonstrated real-world application experience
- Specialized expertise in causal inference methodologies (the systematic approach to identifying cause-and-effect relationships through data analysis)
- Experience with longitudinal data analysis, observational studies, and experimental design
- Proficiency with data visualization platforms (Tableau, Power BI, or similar)
- Strong foundation in data integration, ETL workflows, and database architecture
- Deep understanding of statistical modeling, sales attribution models, and controlled testing frameworks
- Experience with major advertising platforms and walled garden environments (Meta, Google Ads, Amazon, etc.)
- Excellent communication abilities to effectively engage both technical and business audiences
- Master's degree in Data Science, Statistics, Computer Science, or related quantitative field preferred
- Minimum 3+ years of data science experience with emphasis on consumer behavior analysis and sales measurement
- Prior experience with walled garden platform integration is highly valued
Bonus points for:
- Experience in adtech, consumer analytics, or marketing science
- Store-level transaction data experience
- Understanding of privacy-focused measurement techniques
If you have a curious nature and enjoy studying and staying up-to-date, you're the person we're looking for! You'll be working with the latest ad measurement technology, with a blend of technical prowess, creativity, and business skills, and creating solutions with real impact. What are you waiting for? Fill out the form below and apply!
Originally posted on Himalayas