Data Scientist
instahyre
Job Description
- KPI Design and Stakeholder Strategy: Partner with cross-functional stakeholders (e. g., Marketing, Finance) to define and propose business KPIs that are logically sound, reasonably challenging, and easily communicable to non-technical teams.
- Data Engineering and EDA: Clean, preprocess, and validate large, complex datasets (structured/unstructured). Perform deep-dive Exploratory Data Analysis (EDA) to identify patterns, ensure data integrity, and set the initial strategic direction for analysis.
- Personalization and Recommendation: Design and implement recommendation engines to enhance user engagement and brand trust, leveraging both classical and deep learning-based approaches.
- Iterative Model Development: Develop and deploy predictive models, including customer behavior prediction, customer lifetime value (CLV), media mix modeling, and time-series forecasting using Python and PyTorch.
- Advanced Segmentation: Lead customer behavioral analysis projects using unsupervised clustering techniques to drive personalized brand empowerment strategies.
- Continuous Improvement Loops: Systematically identify bottlenecks in model accuracy through rigorous evaluation and error analysis; iterate on model architectures and data features to consistently hit and exceed target KPIs.
- Collaborative Engineering and Privacy: Maintain production-grade code repositories using GitHub, ensuring version control and documentation are integrated into the R& D process while adhering to data privacy and ethical AI practices.
- Cutting-Edge Research: Research and implement state-of-the-art techniques, including LLMs/Generative AI, NLP, and Deep Learning, to enhance business strategies and solve brand empowerment challenges.