Nivel cariera

Middle (2-5 ani), Entry (0-2 ani)

Limbi vorbite

engleză

Adresa/adresele jobului


Responsibilities: 

Conducts advanced data analysis;

Participates in continuous learning process in Machine Learning (with in-house Machine Learning / Deep Learning mentors);

Employs already prepared Machine Learning and Deep Learning models for inferential and predictive experiments;

Prepares visual results, reports and actionable insights based on inferential and predictive models;

Designs experiments, tests hypotheses, and builds models together with advanced AI experts;

 Works with business stakeholders to identify business requirements and expected outcome;

 Collaborates with subject matter experts to identify relevant sources of data within the organization;

 Works with team leaders, project managers, and IT suppliers to solve data analytics problems and documents results and methodologies;

 Works in iterative processes with IT and validates findings;

 Performs experimental design approaches to validate finding or test hypotheses;

 Quantifies accuracy metrics of data analysis;

 Translates analytical and statistical findings into business language and disseminates results to business stakeholders;

Conducts advanced data analysis;

Participates in continuous learning process in Machine Learning (with in-house Machine Learning / Deep Learning mentors);

Employs already prepared Machine Learning and Deep Learning models for inferential and predictive experiments;

 

Core skills needed:

 Skilled in data analysis and data exploration

 Proficient in fundamental statistical data analysis methods

 Proficient in Excel-based data analysis

 Has good knowledge of SQL, capable of extracting and analyzing relational data from relational databases

Understanding capability of complex processes and trends, identify abnormal patterns and behaviors in data and willingness to further develop knowledge in this areas

 Capable of understanding and interpreting complex data visualizations

 Demonstrates the following scientist qualities: clarity, accuracy, precision, relevance, depth, breadth, logic, significance, and fairness

 

Skills at a plus:

 Knowledge of retail specific data models

 Knowledge of multivariate calculus and linear algebra

 Preferable minimal knowledge in Python or R

 Understands the basics (minimal) of machine learning, with a strong focus on classification, regression, and clustering algorithms.