Senior Data Analyst

Short company description

At Evolve today we offer complex Human Resources services, from business consulting to headhunting and recruitment. We have extensive experience in finding talented professionals, for a variety of industries, especially in the IT sector.
We started with a dream: to create a Human Resources company with a strong, unique profile on the market, deeply shaped by our core values: commitment to performance, professionalism, a balanced approach and deep satisfaction for our clients.
From that moment, we nurtured special relationships and we continuously evolved, being flexible, but staying true to our values. We aim higher and higher and we invite you to EVOLVE with us!

Requirements

In this role you you will be consulting with Business Analyst on their data analysis needs, analyzing data using statistical modeling, and presenting your findings.

Your profile

At least 5+years experience in a similar Data Analyst role.
Working experience with Databases, segmentation techniques, descriptive statistics and data visualization;
Good knowledge of SQL, reporting, statistics, analytics, descriptive statistics, hypothesis testing/working scenarios
Ability to analyze, visualize and synthesize information & data;
Knowledge of Python, Matlab, R, SAS or equivalent.
Knowledge in the area of reporting, data cleaning.
Knowledge of statistical population, calculation of variance, covariance and standard deviation, calculation the central tendency of a data set (mean, median and mode).
Analysis of variation (ANOVA type) and Regression analysis.
Knowledge related to at least one reporting tool (eg PowerBI, Cognos, Oracle Reports, etc.).

Responsibilities

Main tasks:

Collaborates with other departments to provide support in the interpretation and application of analysis results.
Interpret the data, contribute to the pre-processing and data processing process, perform the data analysis, analyze the results using statistical techniques and provide reports on this activity.
Develop and apply statistical models to provide relevant insights.
Ensures compliance with the principles of probability theory and statistical inference in the interdisciplinary studies in which it participates.
Apply data science theories and methods to solve problems.
Identifies relationships between variables and data trends.
Apply various sampling techniques in order to build the models that will be studied/tested.
Develops and tests research, selection and processing strategies adapted to the specifics of each discipline/research theme.
Identifies and limits the influence of factors that can distort research results.
Knowledge of EDA (exploratory data analyzes) and descriptive techniques.