Tetra Tech · 5 hours ago

Quantitative Data Analyst, EMSRIE, Remote

Arlington, VA

Full-time

Remote

Mid, Senior Level

$300/d - $550/d

5+ years exp

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ConsultingEnvironmental Engineering

No H1B

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Responsibilities

Create surveys, questionnaires, and other quantitative data collection tools to capture the necessary data for the evaluation, ensure statistical soundness, and minimize potential biases.

Determine appropriate sample sizes and sampling methods crucial for the validity of the evaluation including calculating required sample sizes to achieve sufficient statistical power, designing stratification strategies if needed, and developing methods for random selection of participants.

Process raw data to prepare it for analysis, including identifying and handling missing data, detecting and correcting errors, standardizing variables, and creating derived variables as needed for the analysis.

Perform various types of statistical analyses, including descriptive statistics, inferential statistics, regression analysis, propensity score matching, difference-in-differences analysis, and other advanced techniques appropriate for the evaluation design.

Design and produce charts, graphs, tables, and other visualizations that clearly convey key insights from the analysis, ensuring effective communication of findings to diverse audiences.

Write sections of technical reports detailing the methodologies used, presenting results, and discussing statistical findings including translating complex statistical concepts into language accessible to a broader audience.

Calculate statistical power to ensure that the evaluation can detect meaningful program effects including determining the minimum detectable effect size given the sample size, or conversely, the sample size needed to detect a specific effect size.

Qualification

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Statistical analysisData visualizationImpact evaluationsRPythonSTATAMachine learningSQLRegression analysisCausal inference methodsProbability theoryHypothesis testingExperimental designsQuasi-experimental designsData cleaningSample size determinationFluency in English

Required

Master's degree in statistics, economics, data science, or a related quantitative field, providing a strong foundation in quantitative methods required.

Minimum five years of statistical experience required.

Experience working on impact evaluations or similar research projects, providing practical knowledge of evaluation processes, common challenges, and effective solutions in real-world contexts.

Knowledge of machine learning techniques for predictive modeling and pattern recognition in large datasets, including skills in supervised and unsupervised learning algorithms, feature selection, and model evaluation.

Knowledge in the relevant sector or field in which the impact evaluation will be conducted, such as development economics, public health, or education.

Proficiency in a wide range of techniques such as probability theory, hypothesis testing, regression analysis, causal inference methods, and both experimental and quasi-experimental designs.

Advanced data visualization skills, including the ability to create clear and impactful visual representations of data using relevant software tools.

Strong programming skills, particularly in statistical software such as R, Python, or STATA for data analysis, as well as proficiency in database management using SQL or similar tools.

Strong communication skills, with the ability to explain complex quantitative concepts to non-technical audiences in writing and verbally.

Fluency in English required.