Senior A/B Test Statistical Validation Specialist

Nature Based Solutions; United Arab Emirates; A distancia; AED 360.000 - 480.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

100% remote work

Global collaboration with diverse team

Descripción de la vacante

Nature Based Solutions Group is seeking a Senior A/B Test Statistical Validation Specialist to oversee the statistical design, validation, and interpretation of controlled experiments in a fully remote setup.

The role requires strong expertise in hypothesis testing, power analysis, and Bayesian/frequentist methods, with proficiency in Python or R, SQL, and data visualization tools. You will collaborate with cross-functional teams worldwide.

Formación

• Bachelor's or master's degree in Statistics, Mathematics, Data Science, Economics, or a related quantitative discipline.
• Significant professional experience in statistical analysis, experimentation, or A/B testing.
• Strong understanding of hypothesis testing, statistical power, confidence intervals, and effect-size estimation.
• Experience designing and validating controlled experiments in digital products, marketing, or business environments.
• Knowledge of randomization, sampling methods, experimental bias, and causal inference.
• Proficiency in statistical programming using Python or R.
• Experience working with SQL and large-scale analytical datasets.
• Familiarity with experimentation platforms, analytics tools, and data visualization solutions.
• Ability to evaluate statistical assumptions and identify methodological weaknesses.
• Understanding of multiple testing, sequential analysis, and Bayesian experimentation is advantageous.
• Strong analytical reasoning, attention to detail, and problem-solving skills.
• Excellent written and verbal communication skills.
• Ability to manage multiple experiments and validation projects independently in a remote environment.

Responsabilidades

• Design and validate statistical frameworks for A/B tests and controlled experiments.
• Review experiment hypotheses, success metrics, primary outcomes, and guardrail metrics.
• Assess sample-size requirements, statistical power, minimum detectable effects, and test duration.
• Validate randomization procedures, treatment allocation, and control-group integrity.
• Evaluate statistical assumptions, including independence, distributional characteristics, and variance.
• Apply appropriate statistical tests, confidence intervals, and significance thresholds.
• Identify potential sources of bias, including selection bias, sample-ratio mismatch, and data contamination.
• Review experimental data for missing values, outliers, tracking errors, and inconsistencies.
• Assess the suitability of frequentist and Bayesian testing approaches where appropriate.
• Validate multiple-comparison adjustments, sequential testing methods, and early-stopping procedures.
• Investigate anomalous or inconclusive experiment results and recommend corrective actions.
• Review statistical analysis code, experiment documentation, and reproducibility standards.
• Collaborate with data scientists, product managers, engineers, and business teams.
• Communicate statistical findings, limitations, and recommendations to technical and non-technical stakeholders.
• Develop standardized procedures and quality controls for experimental validation.

Conocimientos

Hypothesis testing

Statistical power

Confidence intervals

Effect size estimation

Analytical thinking

Communication

Remote work management

Educación

Bachelor's degree in Statistics/Mathematics/Data Science or related

Master's degree preferred

Herramientas

Python

R

SQL

Experimentation platforms

Data visualization tools

Descripción del empleo

Job Title: Senior A/B Test Statistical Validation Specialist

Location: United Arab Emirates (Remote) Employment Type: Full-Time Work Arrangement: 100% Remote — Work From Home Level: Senior

About the Role

We are seeking an experienced Senior A/B Test Statistical Validation Specialist to oversee the statistical design, validation, and interpretation of controlled experiments. The successful candidate will ensure that A/B tests are methodologically sound, statistically reliable, and aligned with business objectives. This role involves evaluating experimental designs, validating analytical methods, identifying statistical risks, and translating complex findings into clear recommendations for business and product stakeholders.

Key Responsibilities

• Design and validate statistical frameworks for A/B tests and controlled experiments.
• Review experiment hypotheses, success metrics, primary outcomes, and guardrail metrics.
• Assess sample-size requirements, statistical power, minimum detectable effects, and test duration.
• Validate randomization procedures, treatment allocation, and control-group integrity.
• Evaluate statistical assumptions, including independence, distributional characteristics, and variance.
• Apply appropriate statistical tests, confidence intervals, and significance thresholds.
• Identify potential sources of bias, including selection bias, sample-ratio mismatch, and data contamination.
• Review experimental data for missing values, outliers, tracking errors, and inconsistencies.
• Assess the suitability of frequentist and Bayesian testing approaches where appropriate.
• Validate multiple-comparison adjustments, sequential testing methods, and early-stopping procedures.
• Investigate anomalous or inconclusive experiment results and recommend corrective actions.
• Review statistical analysis code, experiment documentation, and reproducibility standards.
• Collaborate with data scientists, product managers, engineers, and business teams.
• Communicate statistical findings, limitations, and recommendations to technical and non-technical stakeholders.
• Develop standardized procedures and quality controls for experimental validation.

Qualifications and Experience

• Bachelor's or master's degree in Statistics, Mathematics, Data Science, Economics, or a related quantitative discipline.
• Significant professional experience in statistical analysis, experimentation, or A/B testing.
• Strong understanding of hypothesis testing, statistical power, confidence intervals, and effect-size estimation.
• Experience designing and validating controlled experiments in digital products, marketing, or business environments.
• Knowledge of randomization, sampling methods, experimental bias, and causal inference.
• Proficiency in statistical programming using Python or R.
• Experience working with SQL and large-scale analytical datasets.
• Familiarity with experimentation platforms, analytics tools, and data visualization solutions.
• Ability to evaluate statistical assumptions and identify methodological weaknesses.
• Understanding of multiple testing, sequential analysis, and Bayesian experimentation is advantageous.
• Strong analytical reasoning, attention to detail, and problem-solving skills.
• Excellent written and verbal communication skills.
• Ability to manage multiple experiments and validation projects independently in a remote environment.

What We Offer

• 100% remote working arrangement within the stated employment framework.
• Competitive compensation based on qualifications and experience.
• Opportunities to work on complex experimentation and statistical validation projects.
• Professional development and continuous learning opportunities.
• Collaborative environment with multidisciplinary and international teams.