As a Senior Data and Applied Scientist, you will design machine learning models, analyze data, and collaborate across teams to optimize logistics operations.
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.
- 2-6 years of industry experience in building and deploying machine learning solutions and simulations.
- 1-3 years of industry experience in logistics/operations.
- Understanding of linear programming, integer programming, and nonlinear programming
- 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.
- Experience with Git, AWS, and deep learning models is advantageous.
Pattern is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Top Skills
AWS
Git
Numpy
Pandas
Python
Scikit-Learn
SQL
Xgboost
Similar Jobs
Artificial Intelligence • Healthtech • Professional Services • Analytics • Consulting
The R&D Technologist will design and implement innovative clinical data management solutions, conduct requirement gathering, lead Agile meetings, and liaise between clients and project teams in drug development contexts.
Top Skills:
PythonRSAS
Artificial Intelligence • Healthtech • Professional Services • Analytics • Consulting
Lead and manage Power Platform solutions for clients, overseeing development, implementing AI capabilities, and mentoring teams while ensuring quality and project timelines.
Top Skills:
Api IntegrationsAzure AiC#CopilotDataverseDot NetPower AppsPower AutomatePower BIPythonSharepointSQL
Artificial Intelligence • Healthtech • Professional Services • Analytics • Consulting
The role involves Power BI and Power Apps development, managing project phases, collaborating with teams, and mentoring, with a focus on delivering tech solutions that meet client needs.
Top Skills:
AgileCdsDaxEtl ServicesPower AppsPower BIPythonSharepointSQLWaterfall
What you need to know about the Pune Tech Scene
Once a far-out concept, AI is now a tangible force reshaping industries and economies worldwide. While its adoption will automate some roles, AI has created more jobs than it has displaced, with an expected 97 million new roles to be created in the coming years. This is especially true in cities like Pune, which is emerging as a hub for companies eager to leverage this technology to develop solutions that simplify and improve lives in sectors such as education, healthcare, finance, e-commerce and more.