Data Scientist 2

Responsibilities

• Deliver end-to-end Data Science projects including:
• Understanding of business requirements.
• Exploratory data analysis.
• Data processing, aggregating data, feature engineering.
• Building and validating predictive models.
• Explaining model results and insights.
• Use AI, ML, DL techniques such as regression, classification, clustering, tree-based algorithms, support vector machine, and neural networks, recommender system, attribution modeling to address business problems.
• Improve upon existing methodologies by developing new data sources/features, testing model enhancements, and fine-tuning model parameters.
• Provide requirements to develop analytical capabilities, platforms, and pipelines.
• Present insights and recommendations to audiences of varying levels of technical sophistication.
• Automate processes to ensure scalability of solutions by collaborating with cross-functional teams.
• Perform the extraction, transformations, and loading from the source systems and the data lake to the analytics products using independently developed logic.
• Enhance data maturity and integration for Epsilon projects by interacting with operations to standardize the core value-add functionality, enabling a multiplier effect experience working within a collaborative team.
• Challenge the status quo with entrepreneurial innovation in curating new data sources, elevating analytics beyond data reporting and dashboarding to delivering actionable insights.

Qualifications

• Master's or Bachelor's Degree in a quantitative discipline (Statistics, Economics, Mathematics, Data Science, Business Analytics).
• 2-4 years of experience as a Data Scientist deploying Data Science projects.
• 2+ years of hands-on experience in Python, SQL, ML and DL Algorithms.
• Good to have understanding of LLMs, Databricks, Azure DevOps, and Cloud Systems.
• Experience of working with large data sets and developing scalable solutions.
• Knowledge of Automotive Business, and Digital Marketing Campaigns are preferred.
• Ability to work independently and deal with ambiguity.
• Strong analytical and problem-solving skills.
• Excellent presentation and communication skills.
• Strong written and verbal communication skills.
• Highly motivated and collaborative team player with strong interpersonal skills.