Senior Data and Applied Scientist

Pattern; Maharashtra; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Pattern is seeking a Senior Data and Applied Scientist to curate and analyze data and apply machine learning models across the organization, with a focus on logistics and operations. The role involves building predictive models, collaborating with global data science teams, and enhancing data pipelines for robust performance.

Candidates should have 3–6 years in ML, 1–3 years in logistics/operations, and strong Python/SQL skills with Pandas, NumPy, Scikit-Learn, and XGBoost.

Qualifications

• Design and deploy predictive ML models and simulations.
• Strong Python and SQL with Pandas/NumPy/Scikit-Learn/XGBoost.
• Excellent communication across departments and ML knowledge levels.
• Deep understanding of model evaluation metrics.
• Familiarity with linear, tree-based models and optimization concepts.

Responsibilities

• 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, feature engineering, and algorithm tuning.

Skills

Python

SQL

Pandas

NumPy

Scikit-Learn

XGBoost

Education

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

Tools

Git

AWS

Job description

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, NumPy, 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 and identifying potential inconsistencies or verification signals in application materials based on available information. 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.