Manager/Senior Manager - Data Science

Date: Jun 15, 2022

Location: Bangalore, India

Company: Tredence

Job Description

 

  • 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 And Responsibilities

 

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