Innovate to solve the world's most important challenges
Area of Responsibility
% Time Spent
1. Problem Solving
· Gather the requirements from the stakeholder (Analytics Lead; Materials Management team; or other ISC team)
· Develop an understanding on what is the problem and formulate an objective/business goal
· Identify the datasource for solving the problem; Formulate a plan on integrating data
· Data preprocessing and cleaning of data
· Modelling a solution to identify the key problems; discuss with the stakeholders on level of details; frequency of updates
· Propose an automated solution by integrating data from multiple datasources (automatically)
· Proposed solution should be interactive to the user and should be able to tell the story behind the analysis;
· It should be easy to understand for a person with business background ; solution proposed shouldn't just be in terms of numbers but should be in terms of inference from the data
· Once the descriptive anlytic solution is provided , should be able to model solutions which predict such problems in the business
20% to 35%
36% to 50%
2. Integration and Automation .
§ The Analytical solutions provided should be maintained regularly
§ Data Scientist should do data reconciliation; data validation against other data sources and rigorously test the solution against the ERP (SAP) Data
§ The proposed data model should be refined regularly based on the business feedback
§ Should trouble shoot any issues or concerns raised by the business
§ Once the problem is solved; the data scientist should work on automating the solution by integrating data from multiple tools
§ Until the automation is done; he /she should send daily emails by manually creating the reports
§ Should be able to google or contact people with experience to figure out a solution to automate reports
§ Based on the business request should be able to download and integrate data from multiple sources
§ Refine the accuracy of predicting issues/ problems in business; Should be able to devise solutions which show the trend of such actions in history and implicate the impact of such behavior in future
20% to 35%
36% to 50%
3Data maintenance & adhoc Analytics
§ Should develop a strong understanding of datasources and various fields / variables (SAP; TeamGuru; T-codes in SAP; SAP HANA)
§ Should develop strong understanding of key stakeholders for each data source; existing process and update all MORs accordingly
§ Run Daily reports on the analytic solutions provided (automate all such reporting work to concentrate on developement activites)
§ Review Analytical solutions provided
§ Be able to logically judge the situation and provide solutions for any immediate requests (if sufficient guidance is unavailable)
§ Perform adhoc analysis of data and should be agile to adapt based on business needs
§ Prepare Standard work instructions and automate most of the workflows
§ Research Supply chain analytics best practices across industry and discuss to implement them in HBT Business
§ Conduct regular Data Science training and education
20% to 35%
36% to 50%
30 Problem Solving
30 Integration and Automation
40 maintenance & adhoc Analytics
Education level and/or relevant experience(s)
§ Bachelors/Masters Or equivalent qualification in Analytics; Data Warehousing; Data Science.
Knowledge and skills (general and technical)
§ Fluent English with a mindset of storytelling with data
§ Strong Mathematical and Statistical Analytical Skills Required
§ Coding experience for modeling and automating analytical solutions
§ SAP or Other ERP System knowledge an advantage
§ Excellent verbal & written communication skills
Other requirements (licenses, certifications, specialized training, physical or mental abilities required)
· Problem Solving mindset; Solutions provided should be proactive and forward looking (not just based on historical data but on trend) Design thinking; Story telling with data are the key skills
· Timings: Flexible hours; Needs to make sure work is done - no fixed timings
· Should be able work with minimum guidance; should be able to solve problems by seeking help from various Supply Chain functions
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Honeywell is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, or veteran status.
Honeywell is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status.
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