In this role, you will leverage advanced statistical modeling, machine learning, and data analysis techniques to uncover actionable insights, build cutting-edge predictive models, and drive business impact. This is an opportunity to work with diverse datasets, cloud platforms, and innovative tools to solve complex challenges while collaborating with cross-functional teams.

Responsibilities

Apply mathematical, statistical, and machine learning techniques to drive insights and support decision-making
Utilize tools and frameworks like TensorFlow or PyTorch for predictive and prescriptive modeling
Identify, validate, and leverage internal and external data sources to uncover patterns and opportunities
Develop and refine hypotheses, exploring data within analytics sandboxes and evolving models over time
Implement data manipulation and analysis using libraries like Pandas, NumPy, and Scikit-learn
Collaborate with broader teams to ensure proper sourcing, cleaning, and preparation of data for analysis
Manage and optimize datasets within relational databases using SQL and appropriate governance practices
Create and present compelling data visualizations using tools such as Matplotlib, Seaborn, or Plotly
Contribute to the organization’s data strategy by ensuring alignment with data management best practices
Deploy machine learning models into production using cloud solutions like Amazon SageMaker and EC2
Coordinate with engineers and stakeholders to implement scalable solutions for data workloads

Requirements

Minimum 3 years of experience in data science, machine learning, or related fields
Proficiency in Python, with experience in libraries such as Pandas, NumPy, and Scikit-learn
Knowledge of machine learning frameworks like TensorFlow or PyTorch
Skills in cloud platforms like AWS, including tools such as S3 and SageMaker
Experience with big data technologies like Spark, relational databases using SQL, and Jupyter
Familiarity with version control systems including Git
Understanding of natural language processing (NLP) techniques and sentiment analysis methodologies
Qualifications in open-source data science tools, libraries, and frameworks
Exposure to data visualization best practices using Matplotlib, Seaborn, or Plotly
Experience with data governance principles, ensuring compliance and quality

Nice to have

Familiarity with Docker for containerization and deployment workflows
Expertise in Snowflake for advanced analytics and data warehousing
Capability to work with the Atlassian suite, including Bitbucket, JIRA, and Confluence
Understanding of simulation, complex event processing, and scenario-based analysis

We offer