Marketing Analytics & Measurement Specialist

Job Description: Marketing Analytics & Measurement Specialist

Role: Marketing Analytics & Measurement Specialist **Experience:** 5+ Years **Job Type:** Contract-to-Hire (C2H) **Budget:** Up to ₹1.2 Lakh per Month

Role Overview

Acute InfoSoft is looking for an experienced **Marketing Analytics & Measurement Specialist** with strong hands-on expertise in causal inference, incrementality measurement, experimentation, marketing effectiveness, and attribution modelling.

The ideal candidate must be capable of independently designing and executing experiments, building robust measurement methodologies, analysing complex marketing datasets, and translating statistical findings into actionable business recommendations.

This role requires a strong combination of **statistical expertise, advanced SQL/Python programming, experimentation design, and marketing measurement experience**. Candidates with only dashboarding, campaign reporting, or basic digital marketing analytics experience will not be suitable.

## Key Responsibilities

• Design, implement, and evaluate incrementality experiments to measure the true impact of marketing campaigns.
• Develop and execute causal experiments, including A/B testing, geo-lift testing, holdout experiments, and other appropriate test-and-learn methodologies.
• Apply causal inference and statistical techniques to estimate incremental conversions, revenue, customer acquisition, and return on marketing investment.
• Determine appropriate experimental designs based on business objectives, traffic volumes, statistical power, budget, and operational constraints.
• Perform hypothesis testing, sample-size estimation, power analysis, confidence interval analysis, and statistical significance testing.
• Develop, evaluate, customize, and improve marketing attribution models, including multi-touch attribution where appropriate.
• Write advanced SQL queries and Python programs for data extraction, transformation, statistical analysis, experimentation, and measurement automation.
• Identify measurement biases, data quality issues, tracking gaps, selection bias, and confounding factors that can distort marketing performance.
• Build scalable measurement frameworks and improve the efficiency and repeatability of experimentation programmes.
• Adapt measurement methodologies and data pipelines to evolving marketing technology (MarTech) platforms.
• Work with marketing, analytics, data engineering, and product teams to communicate findings and recommend data-driven decisions.
• Support integrations and measurement changes involving **Adjust and Airship**.

## Mandatory Technical Skills

**1. Experimentation & Incrementality**

• Strong hands-on experience designing and analysing incrementality tests.
• Practical knowledge of A/B testing, randomized controlled experiments, holdout groups, and geo-experiments.
• Ability to distinguish correlation from causation and measure the incremental impact of marketing activity.
• Experience interpreting inconclusive experiments and handling contamination, sample-ratio mismatch, and other experimental biases.

**2. Causal Inference & Statistics**

• Strong understanding of causal inference, hypothesis testing, statistical power, confidence intervals, and effect-size estimation.
• Practical experience with methods such as difference-in-differences, regression-based analysis, matching, or synthetic control, where appropriate.
• Ability to select and justify the right statistical methodology for a given business problem.

**3. SQL & Python**

• Advanced SQL skills, including complex joins, CTEs, window functions, aggregations, and analytical data transformations.
• Strong hands-on Python skills for statistical analysis and data manipulation using libraries such as Pandas, NumPy, SciPy, and Statsmodels.
• Ability to develop reusable analytical code and measurement workflows rather than relying exclusively on BI tools.

**4. Marketing Attribution & Effectiveness**

• Experience developing, modifying, or validating custom attribution models.
• Understanding of attribution limitations, conversion journeys, channel interactions, and attribution bias.
• Familiarity with marketing effectiveness measurement, campaign performance evaluation, and incremental ROAS.
• Knowledge of marketing mix modelling (MMM) is an advantage.

**5. MarTech & Measurement Integrations**

• Practical familiarity with mobile measurement and marketing engagement platforms such as Adjust and Airship.
• Understanding of conversion tracking, event instrumentation, campaign attribution data, and measurement data pipelines.
• Ability to investigate discrepancies between tracking platforms and analytical datasets.

## Required Experience

• Minimum 5 years of relevant experience in marketing analytics, experimentation, causal inference, marketing measurement, or applied data science.
• Demonstrable experience independently delivering end-to-end measurement or experimentation projects.
• Strong ability to explain statistical methodology, assumptions, limitations, and business implications.
• Experience working with large datasets and translating analytical results into measurable business outcomes.

## Preferred Qualifications

• Experience in mobile apps, e-commerce, consumer technology, subscription businesses, or performance marketing.
• Exposure to incrementality-based budget allocation and marketing effectiveness optimization.
• Experience automating recurring experiments and measurement workflows.
• Knowledge of cloud data warehouses and modern analytics infrastructure.

## Candidate Evaluation Criteria

Candidates will be assessed on their ability to

• Explain and defend the design of a real incrementality experiment they have delivered.
• Select an appropriate causal measurement methodology for a business scenario.
• Demonstrate advanced SQL and Python skills through practical analytical problems.
• Interpret experimental results and identify statistical or measurement pitfalls.
• Explain how they built, modified, or validated an attribution model.
• Connect analytical findings to marketing investment and business decisions.

**Important:** Candidates must have practical implementation experience, not just theoretical knowledge or exposure to marketing dashboards.

## Ideal Candidate Profile

A technically strong, analytical professional who combines statistical rigour, advanced programming, experimentation expertise, and practical marketing measurement experience. The candidate should be comfortable owning complex analytical problems independently and communicating defensible, business-focused recommendations.