Data Scientist

RESPONSIBILITIES

Gathers, interprets, and manipulates structured and unstructured data to enable analytical solutions for the business.

Selects the appropriate modeling technique and / or technology with consideration to data limitations, application, and business needs.

Develops and deploys models within the Model guidelines and framework.

Composes technical documents for knowledge persistence, risk management, and technical review audiences. Consults with peers for guidance, as needed.

Translates business request(s) into specific analytical questions, executing on the analysis and / or modeling, and communicating outcomes to non-technical business colleagues.

Consults with Data Engineering, IT, the business, and other internal stakeholders to deploy analytical solutions that are aligned with the customer's vision and specifications and consistent with modeling best practices and model risk management standards.

Stay current with emerging trends and technologies in data quality management, data profiling, data cleansing tools and AI / Client.

Collaborate with data governance teams to ensure compliance with regulatory requirements and industry standards related to data quality and privacy.

QUALIFICATIONS

10 to 12 years of relevant experience, and 6+ years of experience in data science, machine learning, quantitative analytics, quality assurance and data management roles

Bachelor's or Master's degree in Computer Science, Information Systems, Statistics, or a related field

Experience in training and validating statistical, physical, machine learning, and other advanced analytics models.

Experience in Time series Forecasting, Classification models, Segmentation, Fraud Detection, NLP, Deep Learning

Proficient in R, Python, SAS, Power BI, Alteryx

Excellent problem-solving, analytical skills and attention to detail, with the ability to identify patterns, trends, and anomalies in data.

Ability to write code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency).

Experience in querying and preprocessing data from structured and / or unstructured databases using query languages such as SQL, HQL, NoSQL, etc.

Experience in working with structured, semi-structured, and unstructured data files such as delimited numeric data files, JSON / XML files, and / or text documents, images, etc.

Familiarity with performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.

Strong communication and collaboration skills, with the ability to effectively interact with technical and non-technical stakeholders.