Tredence | Hiring | Manager Data Science | BigDataKB.com | 44831

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Job Location: Chennai, Gurgaon/Gurugram, Bangalore/Bengaluru

 

  • Graduate degree in a quantitative field (CS, statistics, applied mathematics, machine learning, or related discipline)
  • Good programming skills in Python with strong working knowledge of Python s numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, etc.
  • Experience with SQL, Excel, Tableau/ Power BI, PowerPoint
  • Predictive modeling experience in Python ( Time Series/ Multivariable/ Causal)
  • Experience applying various machine learning techniques and understanding the key parameters that affect their performance
  • Experience of building systems that capture and utilize large data sets to quantify performance via metrics or KPIs
  • Excellent verbal and written communication
  • Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects.

Roles Responsibilities
  1. Lead a team of Data Engineers, Analysts and Data scientists to carry out following activities:
  2. Connect with internal / external POC to understand the business requirements
  3. Coordinate with right POC to gather all relevant data artifacts, anecdotes, and hypothesis
  4. Create project plan and sprints for milestones / deliverables
  5. Spin VM, create and optimize clusters for Data Science workflows
  6. Create data pipelines to ingest data effectively
  7. Assure the quality of data with proactive checks and resolve the gaps
  8. Carry out EDA, Feature Engineering Define performance metrics prior to run relevant ML/DL algorithms
  9. Research whether similar solutions have been already developed before building ML models
  10. Create optimized data models to query relevant data efficiently
  11. Run relevant ML / DL algorithms for business goal seek
  12. Optimize and validate these ML / DL models to scale
  13. Create light applications, simulators, and scenario builders to help business consume the end outputs
  14. Create test cases and test the codes pre-production for possible bugs and resolve these bugs proactively
  15. Integrate and operationalize the models in client ecosystem
  16. Document project artifacts and log failures and exceptions.
  17. Measure, articulate impact of DS projects on business metrics and finetune the workflow based on feedbacks

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