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Open nowPosted 11 hours ago

Senior Data Scientist

Syren Cloud13 open roles

Where
Hyderabad
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Your applicationOpen nowSenior Data ScientistSyren Cloud · Hyderabad

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The clock on this job

Early applications get read.

13.9% of postings close within 7 days. Measured by our own scanner across the market. Syren Cloud postings stay open a median of 12 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.9%7 days
  4. 22.4%14 days
  5. 38.1%30 days
  6. 59.0%60 days
This job: posted 11 hours ago

Syren Cloud median: 12 days open

The posting

About the Role

We're looking for a Data Scientist with strong breadth across classical data science and hands-on depth in forecasting. The ideal candidate can work across the full data science lifecycle - from problem framing and data exploration to modeling and deployment - and brings specific, demonstrable experience with time-series and demand forecasting problems.

Key Responsibilities

  • Work across the full data science lifecycle - problem framing, EDA, feature engineering, modeling, validation, and deployment
  • Build and maintain forecasting models (time-series and demand/sales forecasting) for client and internal use cases
  • Apply classical ML techniques - regression, classification, and clustering - to a range of business problems
  • Perform rigorous EDA and data quality checks to ensure reliable, production-ready datasets
  • Collaborate with clients and internal stakeholders to translate business problems into data science solutions
  • Communicate findings and model outputs clearly to both technical and non-technical audiences
  • Support deployment and monitoring of models in production environments
  • Mentor junior data scientists as needed

Required Skills & Experience

  • 4-6 years of experience in data science/analytics roles with a broad, generalist skill set
  • Strong, hands-on experience with forecasting - time-series methods (ARIMA, Prophet, exponential smoothing) and/or ML-based forecasting approaches
  • Solid grounding in classical ML - regression, classification, clustering, and feature engineering
  • Proficiency in Python and standard data science libraries (pandas, scikit-learn, statsmodels)
  • Experience with SQL and working with large, real-world datasets
  • Experience deploying or operationalizing models, not just notebook-level analysis
  • Strong communication skills - comfortable presenting findings to clients and stakeholders
  • Ability to work independently and manage ambiguous, client-facing problems

Good to Have

  • Experience with cloud platforms (AWS/Azure/GCP)
  • Exposure to MLOps tooling and practices
  • Experience working directly with external clients
  • Awareness of and interest in the latest Gen AI and agentic AI technology, and how it applies to data science workflows
  • Exposure to optimization modeling (e.g., linear/mixed-integer programming, heuristics)
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