Padmi
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data engineering · healthcare claims auditing

Data Science

Delhi NCR · HybridPosted 7 months ago
DataMid-level
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Job Info

  • Job Identification7384
  • Posting Date01/02/2026, 09:01 AM
  • Job RoleData Science-Machine learning Engineer
  • Experience (In Years)3-6

Job Description

We are looking for a Consultant II – Analytics to join our growing team and drive direct marketing performance through data-driven insights. In this role, you will work on end-to-end analytics tasks — from building predictive models and segmentations to uncovering actionable insights and preparing client-ready presentations. This is an exciting opportunity to make an impact on the direct marketing strategies for leading brands in the US.

We are looking for someone who has:

- Strong hands-on skills in Python/R, MS Excel/ PowerPoint, SAS, and SQL (prior experience in SAS is preferred but not mandatory)

- Solid understanding and experience of machine learning techniques such as linear/logistic regression, decision trees, random forests, XGBoost, and customer segmentation

- Excellent communication skills with the ability to present complex technical concepts to business stakeholders

- Strong attention to detail, self-motivation, and a continuous learning mindset

Responsibilities

  • - Build predictive models and segmentation frameworks to support marketing initiatives

  • - Target the top performing segments in the upcoming direct marketing campaigns

  • - Conduct post-campaign analysis, ad-hoc deep dives, and performance reporting

  • - Translate business problems into analytical approaches and actionable solutions

  • - Prepare clear, concise client-facing decks and present findings to business audiences

  • - Deliver high-quality, accurate, and error-free analytical outputs

Qualifications

  • - 2+ years of experience in analytics with a Master’s/PGDM (preferably in Analytics or related major)

  • - OR 3+ years of experience with a Bachelor’s degree (preferably in Analytics or related major)

Required Skills

  • - Good communication skills with the ability to present complex technical concepts to business stakeholders
  • - Solid understanding and experience of machine learning techniques such as linear/logistic regression, decision trees, random forests, XGBoost, and customer segmentation
  • - Strong hands-on skills in Python/R, MS Excel/ PowerPoint, SAS, and SQL (prior experience in SAS is preferred but not mandatory)

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