Senior Data and Applied Scientist

As a Senior Data and Applied Scientist, you will work with Pattern's Data Science team to curate

and analyze data, and apply machine learning models and statistical techniques to solve business

problems across the organization. Most of your work will revolve around logistics and operations.

What You'll Do

Design, build, and maintain predictive machine learning models and simulations to optimize

solutions across Pattern.

Communicate potential model improvements, data needs, and opportunities across relevant

business units and developer teams.

Continuously optimize the quality of our machine learning models.
Conduct research to integrate new data sources, innovate in feature engineering, fine-tune

algorithms, and enhance data pipelines for robust model performance.

Analyze large datasets to extract actionable insights that guide business decisions.
Work closely with data science teams across different regions (US and India), ensuring seamless

collaboration and knowledge sharing.

Follow code standards and best practices.
Perform root cause analysis to determine accuracy defects and drive improvements.

What We're Looking For

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Economics, or a

related field.

3-6 years of industry experience in building and deploying machine learning solutions and

simulations.

1-3 years of industry experience in logistics/operations preferred.
Excellent communication skills (written and verbal) across departments with different levels of

machine learning knowledge.

Strong data manipulation and programming skills in Python and SQL, and hands-on experience

with libraries such as Pandas, Num Py, Scikit-Learn, XGBoost.

Strong problem-solving skills and an ability to analyze complex data.
In-depth expertise in a range of machine learning and statistical techniques, such as linear and

tree-based models, along with understanding of model evaluation metrics.

Understanding of linear programming, integer programming, and nonlinear programming.

Experience with Git, AWS, and deep learning models is advantageous.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.