lead end-to-end initiatives across the full data science lifecycle—from framing ambiguous problems and exploring data to developing, deploying, and continuously improving models in production
partner closely with engineering, product, and business leaders to turn ideas into scalable, high-impact solutions
influence strategy, guide data-informed decision-making at multiple levels of the organization, and help prioritize where data science can drive the most value
play a key role in mentoring others and raising the bar for technical excellence and collaboration

4+ yrs Proven experience in predictive modeling, data science, and analysis in an ML engineer or data scientist role building and deploying ML models or hands on experience developing deep learning models (Required)
4+ yrs Experience with data scripting languages (e.g., SQL, Python, R) (Required)
2+ yrs Experience with big data architecture and pipeline, Hadoop, Hive, Spark, Kafka, etc. (Required)
4+ yrs Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data (Required)
4+ yrs Experience in data visualization (Required)
4+ yrs Experience working with relational database using SQL (Required)
2+ yrs Experience in the telecom industry (Preferred)
Mathematics Calculus, linear algebra, statistics, and probability (Required)
Programming Expertise in Python and SQL (Required)
Machine Learning: Expertise applying machine learning concepts and techniques related to supervised and unsupervised learning (Required)
Business Analysis (Required)
Business Insights (Required)
Critical Thinking (Required)
Data Analysis (Required)
Data Science (Required)
Data Storytelling (Required)
Data Visualization (Required)
Deep Learning (Required)
Generative AI (Required)
Large Language Model (LLM) Fine-Tuning (Required)
Machine Learning (ML) (Required)
Statistical Analysis (Required)

Senior Data Scientist

Key skills