AI-Powered Data Engineer

6 days ago

Nagpur, Maharashtra, India beBeeDataScientist Full time ₹ 90,00,000 - ₹ 2,10,00,000

About Gleantap

We're a customer engagement platform powering fitness, wellness, and service businesses as we evolve into an AI-native platform. Intelligent agents predict churn, upsell opportunities, and automate member engagement.

We're looking for a talented Data Scientist to join our team and help bridge the gap between data engineering and applied machine learning.

The ideal candidate will design and build robust data pipelines, train accurate models, and deploy them into production at scale.

Key Responsibilities
  • Data Pipelines: Develop and implement efficient data pipelines to transform raw events (visits, purchases, campaigns) into actionable features.
  • Label Definition: Define and compute labels (e.g., churn, upsell, lead quality) from historical events.
  • Machine Learning Models: Develop and train ML models (e.g., churn prediction, upsell propensity, lead scoring) using Python (scikit-learn, LightGBM, XGBoost).
  • Real-Time Inference: Build real-time inference services to serve predictions into production systems.
  • Retraining and Monitoring: Set up retraining and monitoring pipelines (Airflow, MLflow, or similar).
  • Integration: Collaborate with backend engineers to integrate model outputs into production workflows.
  • Data Quality: Ensure data quality, reproducibility, and compliance (HIPAA for healthcare customers).
Requirements
  • Experience: 3–5+ years of experience in data science or applied ML.
  • Technical Skills: Strong proficiency in Python, SQL, and one or more ML libraries (scikit-learn, LightGBM, XGBoost, PyTorch).
  • Data Pipelines: Experience with data pipelines (Airflow, dbt, or custom ETL).
  • Event-Driven Systems: Comfortable with event-driven systems (Kafka, Redis, ClickHouse or similar OLAP).
  • ML Lifecycle: Understanding of ML lifecycle: training, serving, monitoring, retraining.
  • Problem-Solving: Strong problem-solving skills and eagerness to work in a dynamic environment.
Nice-to-Haves
  • MLOps Tools: MLOps tools (MLflow, BentoML, Ray Serve).
  • Bandit Algorithms: Experience with bandit algorithms, A/B testing, or uplift modeling.
  • Customer Engagement: Prior work with customer engagement, CRM, or subscription businesses.

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