Manager, Analytics

Data & Analytics Noida, India

Data Analytics and Solutions, Noida, India

Technical Manager– Data Development

 

Department:

Model Development

Objective of the Role:

The candidate will be extensively involved in managing a team of analysts, GIS experts and data leads. The candidate will also be responsible for QA/QC of the data developed by team and will be ensuring smooth delivery to RMS internal stake holders. Maintain and deliver the geospatial data and its components on time with highest quality. Skills in programming, numerical/statistical analysis, computing, databases etc. would add value.

Key Accountabilities & Deliverables: 

  • Administer efficient working of all GIS staff, manage projects and evaluate performance of all employees.
  • Develop a variety of layers and structure for all spatial data and coordinate with Model Dev teams to integrate data into model platforms.
  • Maintain and operate all GIS related products, manage all components of system database and design and ensue achievement of all phases for project and assist in planning.
  • Coordinate with across geography teams, prepare project plans and provide proactive suggestions / recommendations.
  • Forecast and evaluate present trends, anticipate issues and develop efficient procedures to improve overall data quality.
  • Coordinate with database administrators and ensure availability of all GIS applications as per requirement.
  • Responsible for process enhancement, writing functional specifications and ensuring effective utilization of software development team.
  • Understand the project requirements and help software team to build applications.
  • Accountable to develop method/technique to assess the quality of geotechnical datasets
  • Involve in applying geotechnical, geospatial, geostatistical, and other supportive domain knowledge in property specific attributes
  • Provide professional skills necessary for all phases of data analysis, QA/QC, documentation, and presentation.
  • Communicates analytical insights through sophisticated synthesis and packaging of results (Including PPT slides and charts)
  • Serve as an active participant on cross-functional projects, interpreting data, and translating into actionable insights, provide support on ad-hoc analysis and reports. 
  • To be able to develop robust, scalable and maintainable machine learning models to answer business problems against large data sets
  • Good knowledge in Supervised, Unsupervised and Reinforcement learning/algorithms
  • Self-motivated and driven to satisfy intellectual curiosity through the pursuit of learning and development of new skills.

Experience Required:

  • Post Graduate in Geoinformatics, Remote Sensing, Earth Sciences or Graduate in Civil Engineering, Computer Science, Environmental Science from an institute of good repute
  • 8 to 10 years of total experience with probably 5-year experience in developing geospatial data layers for catastrophe risk insurance industry
  • Research, collect, analyze, and consolidate available datasets (Land Use and Land Cover – LULC - layers, building footprints, industrial facility polygons, road networks etc.)
  • Analyze remotely sensed data from airborne, satellites, or ground-based platforms, using image processing software, GIS software, or statistical analysis software.
  • Knowledge of analysis techniques like statistical methodology, numerical techniques, and data manipulation
  • Critical thinking skills and hands on experience in data interpretation, formulating hypotheses and being able to make educated guesses when data may be sparse or unavailable
  • Excellent communication skills and ability to lead the team and drive projects. 

Technical Skills:

  • Strong working knowledge of ESRI GIS software products and hands on exposure to open source platform such as QGIS, GRASS etc.
  • Familiarity with Google Earth Engine, Open street map and SQL Server would be a plus
  • Proficiency in data analysis and data manipulation is required
  • Knowledge of analysis techniques like statistical methodology, numerical techniques, and data manipulation
  • Programming skills in Python, VB.Net, C#, C++, SQL etc. will be an added advantage
  • Quick leaner for new technologies, programming techniques, languages, and operating systems is must
  • Innovate machine learning and deep learning techniques (good to have)