Apply mathematical, statistical, and probability modeling techniques to solve business problems

Use specialized programming languages, tools, and techniques to extract and analyze data

Implement methods such as data mining, machine learning, pattern matching, forecasting, and sentiment analysis

Source, prepare, and clean data to ensure its quality and readiness for analysis

Identify and validate internal and external data sets to exploit their potential for insights

Develop descriptive, diagnostic, predictive, and prescriptive models to generate actionable recommendations

Find, acquire, and ingest new data sources to expand analytical capabilities

Formulate hypotheses and explore data using models and analytics sandboxes

Refine requirements, validate, train, and continuously improve machine learning models over time

Bachelor's degree in Computer Science, Data Science, or a related field

At least 3 years of experience in data science roles

Proficiency in Python for data analysis and machine learning tasks

Experience with Jupyter for creating and sharing data science workflows

Familiarity with Snowflake for data storage and analytics

Hands-on experience with Docker for containerized environments

Knowledge of the Atlassian Suite, including Bitbucket, JIRA, and Confluence

Experience with AWS services for data, analytics, and machine learning, such as S3, EMR, and SageMaker

Strong analytical and critical thinking skills to uncover insights and solve problems

Effective communication skills to collaborate with stakeholders and present findings

Ability to adapt to new tools, techniques, and evolving data landscapes

High attention to detail and time management skills to handle multiple projects and deadlines

A natural curiosity to explore data and uncover hidden patterns

Innovative thinking to develop new models and approaches

Fluent English skills, both written and spoken, at a B2 level or higher

Experience with AWS Neptune for graph database solutions