Data Scientist

Data Scientist Overview

• The Data Scientist role focuses on optimizing workflows for calculating Annualized Contract Value (ACV) across customer bases.
• This position involves end-to-end process ownership, including automation, auditing, calculation logic, and data warehousing.
• Leverage Power BI Semantic Model to enhance data architecture and reporting capabilities.
• Collaborate with cross-functional teams to formalize assumptions and identify process gaps.
• Design and implement scalable solutions to improve business processes and reporting.
• Work in a hybrid environment with opportunities to engage onsite and remotely.
• Contribute to initiatives involving distributed computing frameworks and cloud search technologies.
• Utilize advanced statistical methods and machine learning techniques to drive insights.
• Enhance professional growth in a dynamic and collaborative environment.

Data Scientist Key Responsibilities & Duties

• Develop and optimize workflows for calculating Annualized Contract Value (ACV) across customer bases.
• Automate processes, audit systems, and refine calculation logic to ensure accuracy.
• Manage data warehousing solutions using PostgreSQL and Databricks.
• Enhance reporting capabilities through Power BI and semantic modeling concepts.
• Collaborate with stakeholders to understand product and sales structures.
• Apply statistical methods and machine learning techniques for data analysis and insights.
• Utilize Python, SQL, and data analysis libraries for advanced analytics.
• Implement distributed computing frameworks and cloud search technologies.
• Prioritize tasks effectively in a fast-paced environment to meet project deadlines.

Data Scientist Job Requirements

• Bachelor of Science (BS) degree in a relevant field is required.
• Minimum of 5 years of experience, with 10 years preferred.
• Proficiency in Python, SQL, and data analysis libraries like pandas and NumPy.
• Experience with data visualization tools such as Power BI and Tableau.
• Familiarity with distributed computing frameworks like Spark and Hadoop.
• Strong foundation in statistics and machine learning methods.
• Effective communication skills and ability to collaborate with senior team members.
• Strong project management skills to prioritize tasks in dynamic environments.
• Familiarity with cloud search technologies such as Elasticsearch and Solr.