Role Overview:
We’re seeking a skilled Data Scientist with expertise in SQL, Python, AWS SageMaker, and Machine Learning. You’ll design predictive models, uncover actionable insights, and deploy scalable solutions to recommend optimal customer interactions. This role is ideal for a problem-solver passionate about turning data into strategic value.
Key Responsibilities:
- Model Development: Build, validate, and deploy machine learning models with a focus on Unsupervised Learning Techniques using Python and AWS SageMaker to drive next-best-action decisions.
- Commercial Analytics: Analyze customer segmentation, lifetime value (CLV), and campaign performance to identify high-impact NBA opportunities.
- Cross-functional Collaboration: Partner with marketing, sales, and product teams to align models with business objectives and operational workflows.
- Insight Communication: Translate technical outcomes into actionable recommendations for non-technical stakeholders through visualizations and presentations.
- Continuous Improvement: Stay updated on advancements in AI/ML, cloud technologies, and commercial analytics trends.
Qualifications / Education:
- Bachelor’s/Master’s in Data Science, Computer Science, Statistics, or a related field.
Experience:
- 5-8 years in data science, with a focus on commercial/customer analytics (e.g., pharma, retail, healthcare, e-commerce, or B2B sectors).
Technical Skills:
- Proficiency in SQL (complex queries, optimization) and Python (Pandas, NumPy, Scikit-learn).
- Hands-on experience with AWS SageMaker (model training, deployment) and cloud services (S3, Lambda, EC2).
Analytical Mindset: Strong problem-solving skills with the ability to derive insights from ambiguous data.
Communication: Ability to articulate technical concepts to business stakeholders.
Preferred Qualifications
- AWS Certified Machine Learning Specialty or similar certifications.
- Exposure to BI tools (Tableau, Power BI) for dashboarding.
Pay: ₹2,000,000.00 - ₹3,000,000.00 per year
Benefits:
- Flexible schedule
- Paid sick time
- Paid time off
Work Location: Remote
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