Apply mathematical, statistical, and machine learning methods to derive insights and support decisions

Leverage frameworks like TensorFlow and PyTorch for predictive and prescriptive model development

Identify and validate internal and external data sources to uncover patterns and business opportunities

Formulate and test hypotheses by working with analytics sandboxes and enhancing models iteratively

Utilize tools such as Pandas, NumPy, and Scikit-learn for data manipulation and analysis

Collaborate with cross-functional teams to prepare and clean data effectively for analysis

Manage datasets within relational databases using SQL and ensure compliance with governance standards

Create impactful data visualizations using Matplotlib, Seaborn, or Plotly

Align data models and practices with organizational data strategy and adhere to best practices

Deploy machine learning models into production environments via cloud platforms like Amazon SageMaker and EC2

Partner with engineers and stakeholders to implement scalable solutions for handling data workloads

At least 5 years of experience in data science, machine learning, or applicable fields

Proficiency in Python, including use of libraries such as Pandas, NumPy, and Scikit-learn

Knowledge of machine learning frameworks, such as TensorFlow or PyTorch

Skills in cloud platforms like AWS, including services like S3 and SageMaker

Background in using big data technologies like Spark, relational databases with SQL, and Jupyter

Familiarity with version control tools such as Git

Understanding of natural language processing (NLP) techniques and sentiment analysis approaches

Proficiency in open-source data science tools, libraries, and frameworks

Competency in data visualization standards with tools like Matplotlib, Seaborn, or Plotly

Familiarity with data governance principles to ensure compliance and data quality

Knowledge of Docker for containerization and deployment processes

Expertise in Snowflake for advanced analytics and data warehousing

Flexibility to use tools in the Atlassian suite, including Bitbucket, JIRA, and Confluence

Understanding of simulation methods, complex event processing, and scenario-driven analytics