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**Company Description**
Technology is our how.

And people are our why.

For over two decades, we have been harnessing technology to drive meaningful change.

By combining world-class engineering, industry expertise and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses.

From prototype to real-world impact - be part of a global shift by doing work that matters.

Our data team has expertise across engineering, analysis, architecture, modeling, machine learning, artificial intelligence, and data science.

This discipline is responsible for transforming raw data into actionable insights, building robust data infrastructures, and enabling data-driven decision-making and innovation through advanced analytics and predictive modeling.

As a data should be able engage with these questions:
1) Explain the assumptions underlying a linear regression and why they matter.

2) How would you think about modelling the purchase decision for a personal computer (eg to build a recommendation engine)?

3) Explain the difference between precision and recall, and how one balances between them.

4) Explain Bayes Theorem.

Compare Bayesian predictions with those from a Neural Net model.
**Qualifications**
- Key skills:
1.

Methodology: Understanding pattern learning algorithms for regression and classification.

2.

Modelling:



Finding ways to represent the real world in simple ways that can be solved using numbers.

3.

Measurement: Defining and tracking the right metrics to evaluate performance.

4.

Probability (Advanced): Using probability theory to improve models and decision-making.

Typical Output: Models that predict behaviour with a high precision.

Typical Technologies: Jupyter Notebook, Scikit Learn, Tensor

Flow/Torch

Typical degree: Maths, Science

**Additional Information**
Discover some of the integral benefits that empower our people to become the best version of themselves:

- ** Finance**:Competitive salary package, share plan, company performance bonuses, value-based recognition awards, referral bonus;
- ** Career Development**: Career coaching, global career opportunities, non-linear career paths, internal development programmes for management and technical leadership;
- ** Learning Opportunities**: Complex projects, rotations, internal tech communities, training, certifications, coaching, online learning platforms subscriptions, pass-it-on sessions, workshops, conferences;
- ** Work-Life Balance**:Hybrid work and flexible working hours, employee assistance programme;
- ** Health**: Global internal wellbeing programme, access to wellbeing apps;
- ** Community**: Integral internal tech communities, hobby clubs and interest groups, inclusion and diversity programmes, events and celebrations.

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📌 Data Scientist (Rosario) (Argentina)
🏢 Endava
📍 Argentina