Data Innovation Specialist

7 days ago

Palakkad, Kerala, India beBeeMachineLearning Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

About the Role:

We are seeking a skilled Data Engineer to bridge the gap between data engineering and applied machine learning, building pipelines, training models, and deploying them at scale.

  • Design and build scalable data pipelines to transform raw events into usable features.
  • Develop and train machine learning models using Python (scikit-learn, LightGBM, XGBoost) for tasks like churn prediction, upsell propensity, and lead scoring.
  • Build real-time inference services to serve predictions into production systems.
  • Collaborate with backend engineers to integrate model outputs into workflows.

Key Requirements:

  • 3–5+ years of experience in data engineering or applied ML.
  • Strong proficiency in Python, SQL, and one or more ML libraries.
  • Experience with data pipelines and event-driven systems.
  • Understanding of the ML lifecycle: training, serving, monitoring, retraining.

Nice-to-Haves:

  • MLOps tools like MLflow.
  • Experience with bandit algorithms, A/B testing, or uplift modeling.

A strong problem-solving mindset and eagerness to work in a startup environment are essential for this role.

Job Description Overview

The ideal candidate will have a solid understanding of data engineering principles and applied machine learning concepts. They will be responsible for designing, building, and maintaining large-scale data pipelines, as well as developing and training machine learning models using various Python libraries. The successful candidate will also have excellent collaboration skills and be able to integrate model outputs into production systems.

Required Skills and Qualifications

Data Engineering and Machine Learning Expertise

  • Proven experience in data engineering and applied machine learning.
  • Strong knowledge of Python, SQL, and one or more ML libraries.
  • Experience with data pipelines and event-driven systems.

Technical Requirements

  • Proficiency in MLOps tools like MLflow.
  • Experience with bandit algorithms, A/B testing, or uplift modeling.

Soft Skills

  • Excellent problem-solving skills and ability to work independently.
  • Strong communication and collaboration skills.

Bonus Points:

  • Knowledge of cloud-based technologies like AWS or GCP.

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