Data Scientist

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

For our business partner, one of the largest integrator of IT and physical security solutions for national and European critical infrastructure, we are looking for a motivated Data Scientist to analyze large amounts of raw information to find patterns that will help improve the business decision making.

Requirements:

5+ years of professional experience in a Data Scientist or Data Analyst.
Proficiency in Python or R for analysis and modeling.
Experience with data processing tools (Pandas, Numpy in Python; dplyr, tidyverse in R).
Knowledge of working with relational databases and NoSQL (SQL, MongoDB, etc.).
Familiarity with machine learning techniques and associated packages (Scikit learn, TensorFlow).
Experience with visualization tools (Tableau, Power BI, Matplotlib, Seaborn, ggplot2).
Proficiency using data mining tools and APIs.
Analytical mind and business acumen
Problem-solving aptitude.
Excellent communication and presentation skills.
BSc/BA in Computer Science, Engineering or relevant field.

Responsibilities

Responsibilities:

Data collection and processing: extract and process data from various sources (APIs, databases, files) using Python, R or other similar languages.
Exploratory data analysis: identifies hidden trends and patterns in complex data sets, performing a detailed exploratory analysis.
Predictive Modeling: develop, validate and optimize predictive and statistical models for solving business problems using machine learning techniques.
Data presentation and visualization: create attractive and easy-to-understand visualizations with the help of tools like Tableau, Power BI, Matplotlib, Seaborn or ggplot2 to communicate analytical results to non-technical teams.
Process optimization: automate data collection and analysis workflows,
implementing efficient and scalable solutions.
Cross-functional collaboration: works closely with engineering, marketing, sales teams and other departments to understand requirements and provide data-driven solutions.
Monitoring and reporting: Provide regular reports and analysis to support decisions strategic of the company.