Job Description:

Core Responsibilities:

• Collaborate with the senior data science team to improve global market share estimates, model customer trends, and optimize ecommerce strategies.

• Use predictive modeling techniques to support the data science team, ensuring data-backed recommendations.

• Manage existing models and work on their continuous improvement by researching new data sources, fine-tuning algorithms, and building better data pipelines.

• Take charge of feature selection, model fine-tuning, and regression analyses.

• Allocate efforts between data science (80%) and Machine Learning Operations (MLOps) (20%) to facilitate seamless model deployment and operational efficiency.

Requirements:

• Knowledge of machine learning techniques and understanding of model evaluation metrics.

• 3-5 years of experience building Machine Learning solutions..

• Bachelor's or Master's in Data Science, Computer Science, Statistics, or a related field.

• Familiarity with Python for data modeling, cleaning, and visualization.

• Experience with SQL for querying databases and managing data workflows.

• Strong problem-solving skills and an ability to analyze complex data.

Company Culture:

We're looking for individuals who are:

• Game Changers: Open-minded problem solvers with innovative ideas.

• Data Fanatics: Love exploring data, finding patterns, and building actionable solutions.

• Partner Obsessed: Understand partner needs and deliver results exceeding expectations.

• Team of Doers: Value accountability and uplift teammates.

How to Succeed with Us:

• Embrace Pattern's core values by diving deep into issues, proactively finding solutions, and managing your projects with creativity and accountability.

Why Work at Pattern?

Pattern offers:

• Flexible working hours

• Competitive pay and benefits

• Collaborative and fast-paced work environment

• Career growth opportunities

• A supportive and inclusive culture

Pattern is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.