Position: Senior Data Scientist Т500
Company: PSRCompany
Category: Data Science
Experience required: 5y
English level: intermediate

**Company:**  Headquartered in San Francisco, CA, our 500+ team members work remotely throughout the world, including India, the Netherlands, Paris, Spain, Australia, and the US. 

	**Product** a subscription billing and revenue management platform powering some of the fastest-growing brands around the world today

	**Rеquirеmеnts :**

- 5 + years of experience manipulating data sets and building statistical models, with a Bachelor’s/Master’s/PhD degree in Statistics, Mathematics, Computer Science or another quantitative field
-  Good applied statistics skills such as distributions, statistical testing, regression.
- Good scripting and programming skills. 
- Experience using statistical computer languages, Python, PySpark, R, SQL to manipulate data and draw insights from large data sets.
- Excellent understanding of machine learning techniques and algorithms, such as- NN, Naive Bayes, SVM, Decision Forests, artificial neur.

	**Areas of Responsibility:**

1. Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
2. Develop a use case roadmap for a problem area or capability for the business. Frame the business problem into a Data Science or modelling problem.
3. Extract data from multiple sources. Mine and analyze data from company databases to drive optimization and improvement of products.
4. Work as the data strategist, identifying and integrating new datasets that can be leveraged through our product capabilities and working closely with the engineering team to strategize and execute the development of data products.
5. Enhance data collection procedures to include information that is relevant for building analytic systems. Processing, cleansing, and verifying the integrity of data used for analysis. Undertake to preprocess of structured and unstructured data.
6. Run data exploration to understand relationships and patterns within the data, develop data visualisation to represent and be able to demonstrate the relationships identified from data exploration.
7. Data mining using state-of-the-art methods. Selecting features, building and optimizing classifiers using machine learning techniques.
8. Refine and deepen understanding of the algorithmic and inferential aspects of statistical analysis. Evaluate new algorithms from the latest research and develop intuition about the problems for which they are likely to improve the state of the practice.
9. Build training pipelines for the production environment. Develop and execute a plan for continuous iteration and refinement of a new model.
10. Provide inputs for design, quality assurance parameters and support implementation for the model in an online environment.
11. Provide inputs and determine infra requirements and infra management for model deployment.
12. Lead debugging of data pipelines and model behaviour in the production environment. Develop dashboards to enable easy tracking and communication of model impact.

	**Thе соmpаny оffеrs:  **

- Salary up to $6300