Data Scientist Ssr

**About Fligoo**

Fligoo is an emerging leader in the Enterprise AI category, having built a technology architecture and suite of products that enable rapid development, deployment, and scaling across large enterprises.

At the moment, we are developing the next generation of AI technology for the Wealth Management and Financial Services industries. Fligoo’s technology leverages AI to allow the most important firms in the world to increase wallet share, predict client attrition, retain financial advisors, increase ROE, among others, significantly growing and protecting AUM. Companies we partner with include Wells Fargo, Cetera, Broadridge, PNC, JPMorgan, among others.

With the acquisition of Mobi To Buy and with offices around the globe in San Francisco, New York, São Paulo, Rio de Janeiro and Córdoba, Fligoo is currently one of the biggest Artificial Intelligence companies in the world.

Our long term vision is to become the most recognized technology company through our work helping our clients improve people’s lives offering solutions to complex problems by leveraging the most valuable asset of our time: data.

**About Position**

Overview

Location: Córdoba (not fully remote).

Position: Full-Time

**Job Purpose**

The **Data Scientist** is responsible for analyzing data sources in a business context in order to propose and implement an analytic approach to solve a business problem. The ideal player is a competent data wrangler with broad experience in several domains, who enjoys analyzing and solving problems. He or she will translate data findings into business insights, so the data scientist must be comfortable by interacting with data and getting correct conclusions from them, as well as implementing a proper analytic task to solve the problem. The Data Scientist will provide support on tasks related to data preparation, help to define and implement the analytic tasks, and guide during the development and deployment of a Data Science solution.

**Responsibilities**:

- Maintain communication with the stakeholder to understand the business and the pain points raised by the client.
- Define required data to address the pain point and design a solution that adds value to the business. Process the data in the most effective way (Using AWS tools like S3, Athena, Jupyter Notebooks to understand and process data).
- Developing an EDA that helps us to validate data with our client and raise insights and results through data story-telling resources.
- Identifying which kind of problem we face (classification, regression, time series, etc), and selecting the best solution approach to add value in the shortest time.
- Implement data processing and feature engineering to disponibility data before starting training and testing the model.
- Assess the effectiveness of data by conducting data quality checks.
- Design, build, tune and test algorithms and deploy the models. Is crucial to use best practices that allow you to reproduce the same result in the test and production environment.
- Developing a strategy to validate the model’s results in production.

**Qualifications**:
1. Academic training
- Degree in Computer Science, System Engineering, Statistics, Mathematics or other quantitative fields.
- A Master's or Ph.D. in those fields is a plus.

2. Technical Skills
- Experience with data science toolkits, such as Python, Jupyter notebooks, Spark or R. Knowledge of OOP paradigm.
- Experience with Python data science libraries such as **Pandas**, Numpy, Scikit-learn, keras, XGBoost and LigthGBM (knowing Keras, PyTorch, or TensorFlow is a plus).
- Experience with data visualizations tools such as Matplotlib, Plotly, Seaborn or GGPlot.
- Experience with AWS cloud infrastructure (i.e. S3, SageMaker, Athena, Lambdas, etc.)
- Knowledge of the Scrum framework for project management. Proficiency in using task management tools like Trello or Jira.
- Experience of code versioning through a system like Git, or Bitbucket.
- Virtualization (Docker).

3. Other Skills
- Advanced English. Able to participate in an extended discussion on a variety of social and technical topics with only occasional disruptions, hesitations, or pauses. Can use complex English grammar structures and sentences to narrate and describe at a level nearly comparable to native speakers.

Experience
- 1+ years working with real-life projects.
- 1+ years performing project tasks and bug tracking on some platforms (e.g. JIRA, Trello).
- 2+ years performing this kind of analytics over real data sources:

- Descriptive Analytics.
- Diagnostic Analytics.
- Prescriptive Analytics.
- 2+ years performing this task over real data sources.
- 2+ years performing basic charts on real data sources:

- Descriptors of distributions of values (e.g. box-plot, histogram, pie-plot).
- Correlation to a target variable (e.g. scatter, correlation matrix).
- Time series plots.
- Variable importance.
- Correct reporting in terms of business language.
- Feature Extract