This role involves leveraging advanced statistical models, machine learning, and data analysis to extract actionable insights, create predictive models, and influence business outcomes. It offers an exciting opportunity to engage with diverse datasets, cloud technologies, and modern tools to solve challenging problems while collaborating with cross-functional stakeholders.

Responsibilities

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

Requirements

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

Nice to have

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

We offer