Data Scientist [Multiple Positions Available]

DESCRIPTION:

Duties: Utilize data analytics to generate actionable insights that support business objectives.

Apply advanced data analysis techniques to identify trends, patterns, and opportunities within large data sets.

Develop and implement data models to predict future outcomes and inform strategic decisions.

Employ machine learning techniques to enhance data analysis and predictive capabilities.

Design, train, and validate machine learning models to improve the accuracy and efficiency of data-driven insights.

Integrate machine learning algorithms into existing data processes to automate and optimize analytical tasks.

Provide strategic guidance to business partners based on data-driven insights.

Present clear and concise recommendations derived from data analysis to inform business strategies and initiatives.

Collaborate with business partners to understand their needs and tailor data insights to support their specific goals.

Support the achievement of the Firm's strategic goals and objectives through data-driven decision-making.

Align data analytics efforts with the Firm's overall strategic plan to ensure that insights contribute to key business priorities.

Monitor and evaluate the impact of data-driven recommendations on business performance and adjust strategies as needed.

QUALIFICATIONS:

Minimum education and experience required: Master's degree in Analytics, Statistics, Mathematics, Data Science or related field of study plus three (3) years of experience in the job offered or as Data Scientist, Data Science Apprentice, or related occupation.

Skills Required: This position requires three (3) years of experience with the following: Leading full-cycle analytics projects using CRISP DM methodology, including gathering requirements from business stakeholders, preparing ETL workflow and cleaning data using SQL, Python, Hadoop, Teradata SQL, and Snowflake Data Cloud, building analysis and validating results, and assessing business impact; Manipulating datasets using software and platforms including Python, SQL, Hadoop, PySpark, Alteryx, Snowflake, and Teradata SQL to create bespoke analytical record; Developing automated scripts using Python & PySpark for data quality checks, and orchestration via Alteryx; Implementing and enforcing data regulation controls, ensuring proper use and thorough documentation of the analytical process with Jira; Building and deploying supervised machine learning models including classification models using Python, including Random Forests, Gradient Boosting Machines, and Decision Trees techniques to create actionable customer personas and compile feature importance analysis; Applying unsupervised learning methods, including K-Means Clustering, Hierarchical Clustering, Principal Component Analysis (PCA), & Gaussian mixture Models (GMM), to create unbiased data lead customer profile segments and recommend optimal price bands; Building price elasticity models using Regression methods and Support Vector Machines...