Sutherland Global - Senior Data Scientist - Big Data (3-6 yrs)

Company Description :

At Sutherland, we are a leading investment and financial advisory firm and a global business and digital transformation partner specializing in Artificial Intelligence, Automation, Cloud engineering, and Advanced analytics.

We work across various industries including Healthcare, Insurance, Banking & Financial Services, Communications, Technology, and more.

Our innovative solutions and patented technologies drive digital transformation and business process excellence, delivered through a seamless "as a service" model.

Role Description :

We are seeking a professional to lead and execute end-to-end data projects with- big data, unstructured, and structured datasets- in high-impact financial services and research environment.

The ideal candidate is a data science expert/ experienced data scientist, with exposure and awareness of data engineering concepts so as to collaborate cross functionally with data engineers, product managers, internal and external stakeholders to successfully drive project execution.

With experience in team leadership and delivering- diagnostic, predictive, and prescriptive insights and data solutions, the individual along with one's team shall drive significant KPI improvements and competitive differentiation for the stakeholders.

You should be a problem solver who thrives in dynamic environments, skilled in organizing, analyzing, and identifying opportunities and risks in data, especially in financial landscapes.

You will be collaborating across functions to deliver actionable insights for the largest and top hedge funds, asset management firms, banks- and companies.

Experience in- productizing data solutions and building scalable and reusable solutions- is a huge plus.

Experience : 3 to 6 years.

Qualifications :

- Data normalization, pre-processing and cleaning.

- NLP and Unstructured Data Processing.

- Feature Engineering, Entity Resolution, Clustering, and Classification.

- Data modeling.

- Hands on querying SQL and NoSQL databases.

- Machine Learning Models (e.g, Random Forest, Time Series Analysis, decision trees, Linear and nonlinear regression, etc.

- Statistical Analysis and Hypothesis Testing.

- Geospatial Data Analysis and Visualization.

Programming Proficiency :

- Hands on experience with Python, R and relevant libraries and tools used in data analysis and engineering.

- Experience with Java, Scala and relevant libraries is a plus.