Data Science/AI Lead

Role Overview:

We're looking for a Data Science and Engineering Lead to optimize our lead management and sales conversion processes through advanced analytics and predictive modeling. The ideal candidate will bridge the gap between business objectives and technical solutions, leading a team of analysts to deliver actionable insights and deployable models.

Key Responsibilities:
- Design and implement end-to-end machine learning solutions to optimize lead quality scoring,
lead prioritization, and conversion prediction.
- Develop analytical frameworks to understand lead behavior patterns, dropout points, and
conversion drivers across the sales funnel.
- Create automated reporting systems and dashboards for real-time monitoring of key
performance indicators (KPIs) in the sales process.
- Lead the development of recommendation engines for personalized communication strategies
based on prospect behavior and characteristics.
- Collaborate with the sales and marketing teams to identify opportunities for process
optimization and automation.
- Guide the implementation of A/B testing frameworks to optimize tele-calling scripts and
communication strategies.
- Build and maintain ETL pipelines for processing sales and lead data from multiple sources.
- Mentor and manage a team of data scientists and analysts, ensuring best practices in code
quality and model deployment.

Required Qualifications:
- 5+ years of experience in data science, with at least 2 years in a lead role.
- Strong background in developing and deploying machine learning models, particularly in sales
or lead conversion optimization.
- Expertise in Python, SQL, and data visualization tools (Power BI, Tableau)
- Experience with ML Ops and model deployment in production environments.
- Proven track record of driving business impact through data science initiatives.
- Strong understanding of lead management systems and sales processes.

Preferred Qualifications:
- Experience in the education sector or similar B2C sales environments.
- Knowledge of CRM systems and call center operations.
- Familiarity with cloud platforms (AWS/Azure).
- Experience with real-time prediction systems.
- Understanding of statistical experimentation and causal inference.