Junior Data Scientist

hace 4 días


Córdoba, Argentina Fligoo A tiempo completo

About Fligoo Fligoo is developing the next generation of AI technology for large customer‑base enterprises. Fligoo’s technology leverages AI to allow the most important firms in the world understand their customers, to increase sales, predict client attrition, retain advisors, increase ROI, among others, significantly growing and protecting assets. Companies we partner with include Wells Fargo, Basf, Broadridge, OI, TIM, among others. 2‑min video on our AI applied to the Wealth Management industry: About Position Overview Location: Córdoba (Hybrid: 3 days at office, 2 days remote). Position: Full‑Time. The Data Scientist Junior will be responsible for learning and applying data science methodologies in a business context to address real‑world challenges. Under the guidance of experienced data scientists, the trainee will contribute to analytic approaches, perform data analyses, and transform findings into valuable business insights. The role aims to cultivate foundational skills in data science through practical applications and collaboration within a dynamic team. Responsibilities Contribute to defining hypotheses and proposing analytic approaches based on available data. Collaborate on the development and execution of tests to validate hypotheses. Work on understanding data sources and extracting relevant information. Collaborate to perform data quality checks to ensure the effectiveness and reliability of data. Learn the definition of feature extraction schemas in collaboration with the team. Contribute to communicate findings and results through effective data storytelling resources. Assist in validating running solutions through hypothesis testing. Qualifications Currently pursuing a degree in Computer Science, Statistics, Mathematics or other quantitative fields – Desired Technical Skills Proficiency with Python Basic understanding of Python libraries: Pandas, Numpy, Matplotlib, Seaborn, GGPlot. Knowledge of machine learning libraries: Scikit‑learn, XGBoost, Keras. Exposure to data visualization tools and frameworks. Familiarity with Linux/MacOS/Windows operating systems. Desirable: Exposure to project task management platforms (e.g., JIRA, Trello). Desirable: Familiarity with code versioning using systems like Git. Desirable: Understanding of testing methodologies (e.g., pytest). Desirable: Awareness of virtualization concepts, such as Docker. Other Skills Developing effective communication skills, both written and verbal, especially in discussing technical subjects. Demonstrating a strong interest and aptitude for learning new technologies and methodologies. Intermediate English proficiency, enabling participation in discussions on technical topics. Experience (Desirable) No specific prior professional experience is required. Understanding of supervised and unsupervised learning concepts. Exposure to tabular data, time series, and tree‑based algorithms (e.g., Random Forest, Gradient Boosting Machines). Exposure to communication tasks related to presenting analytic results. Familiarity or exposure to descriptive, diagnostic and prescriptive analytics. Understanding of correlation analysis techniques (e.g., scatter plots, correlation matrices). Basic familiarity with time series plots and variable importance. Exposure to A/B testing campaigns is a plus. #BuenaOndaSiempre #RevolutionizingWealthManagement #J-18808-Ljbffr



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