Senior Data Scientist

Responsibilities:

• Perform hands-on analysis of large volumes of web analytics, transactions, customer data, and second- and third-party data. Work with complex data structures, manipulate and cleanse data, and perform statistical analysis.
• Design and implement machine learning models using Spark ML, Python, MapReduce, Hive, HDFS, Spring, Hibernate, and Java.
• Design and implement deep neural network models using TensorFlow, PyTorch, Keras, and Python.
• Create engaging and meaningful data visualizations of findings linked to clear client business impact.
• Develop machine learning pipelines with big data design principles in MS Azure cloud using Azure Data Factory.
• Own end-to-end implementations of multiple marketing machine learning models such as churn, CLV, propensity, and affinity models.
• Exposure to Gen AI infrastructure using RAG, Langchain, and agentic workflows is a plus.

Requirements:

• Experience with large-scale distributed databases and computing systems like Hadoop, HDInsight, or DataBricks.
• Strong passion for understanding key business problems, bringing together a team to understand data/instrumentation needs and/or mine through data to unearth deep insights into customer experiences.
• Proven capability to deliver end-to-end analyses by asking the right questions, extracting data, and building predictive models to ensure actionable results.
• Expertise in predictive analytics/statistical modeling/data mining/machine learning algorithms and techniques (classification, clustering, regression, multivariate testing).
• Excellent communication and interpersonal skills with an ability to communicate ideas.
• An MS in Computer Science, Math, or Physics or equivalent education/professional experience is required.
• 6-8 years of total IT experience with 5+ years in a data science role with demonstrable experience.
• Deep experience in machine learning.
• Strong experience in at least one programming language (i. e., Python, R).
• Understanding and experience working with cloud infrastructure services like Azure and Amazon Web Services. Azure preferred.
• Experience working with code repositories and continuous integration (i. e., Git, Jenkins, etc. ).
• Strong passion for understanding key business problems, bringing together the team to understand data/instrumentation needs and/or mine through data to unearth deep insights into customer experiences.
• Excellent communication and interpersonal skills with an ability to communicate ideas, insights, and complicated analysis effectively at all organizational levels, including engineering leadership.