The Role
Lead the data platform, pipelines, semantic data model, monthly savings/productivity reporting and low-code ideation application. Build and deploy predictive models, ensure data quality and governance, provide actionable insights to senior leaders, and manage and grow a cross-functional data engineering, analytics and data science team.
Summary Generated by Built In
As a Sr Manager Data Science and Engineering here at Honeywell Technologies, you will lead the data platform, the monthly reporting cycle, the business ideation application and the analytical insights that enable margin expansion across Honeywell Technologies. You will be accountable for the accuracy and timeliness of the Productivity and Savings Reports, your ability to drive Digitalization of our VECE Ideation & Execution processes, as well as generating action-oriented insights for senior leadership.
You will report directly to our Director Data Science and Transformation, and you will work out of our Monterrey, Mexico location on a hybrid work schedule.
- Own the data model behind ideation and savings: the definitions, dimensions and history that make region, site, savings avenue, category, stage and value consistent globally so any metric can be decomposed, and any model can be trained on it.
- Lead the design, delivery and daily operation of the data pipelines and platform supplying reporting and analytics from approximately 10 source systems, including data quality, access governance and cloud cost management.
- Partner with senior engineering and operations leaders to explain KPI performance at a level they can act on. When a top-level metric misses, break it down until the cause is precise which region, which site, which savings avenue, which category, which stage of the funnel and state what needs to adjust and who owns it.
- Build and own the predictive models supporting ideation and execution likelihood of implementation, savings realization, project delay risk and year-end attainment forecasting including validation against actual outcomes, deployment to the business and ongoing accuracy monitoring.
- Own the monthly savings and productivity reporting cycle end to end close calendar, data validation, reconciliation with Finance, on-time delivery of the leadership pack and reduce the manual effort in it every quarter, demonstrating the reduction with data.
- Own the low-code business application used as the official record for idea and savings tracking, including release management, user support across sites, and management of the external development partner.
- Deliver the analytics that measure the ideation and savings pipeline by site and region and develop automated tools such as duplicate idea detection and project delay warnings.
- Set and enforce data engineering standards for the team, including code review, automated testing, release management and incident response.
- Lead, coach and grow a team of data engineers, analysts and data scientists, including hiring, capacity planning, performance management and succession
- Drive continuous improvement of the reporting cycle, reducing manual effort each quarter and demonstrating the reduction with data.
MUST HAVE
- Minimum of 10-12 years of experience in data engineering, analytics or data science, including a minimum of 5 years directly leading technical teams including hiring, developing and managing performance.
- Hands-on experience designing and operating production data pipelines on a cloud platform, including cost management, with current working proficiency in SQL and Python.
- Experience building and deploying predictive models in production — classification, regression, gradient boosting or time-series forecasting including validation against actual outcomes and monitoring after deployment.
- Experience designing and deploying data models or semantic layers used across a business, including responsibility for definitions, dimensions and their consistent application.
- Demonstrated ability to diagnose why a business metric is underperforming and identify the specific segment driving it, and to present that to senior leaders with a recommendation.
- Experience owning a recurring monthly or quarterly reporting cycle with fixed deadlines, including reconciliation to financial reporting and sign-off with Finance.
- Fluency in English and Spanish, written and spoken.
WE VALUE
- Bachelor’s degree in Engineering, Computer Science, Information Systems or a related discipline. Advanced degree is a plus.
- Experience with Microsoft Azure and Databricks, Power BI and PostgreSQL.
- Experience digitalizing a manual business process end to end, replacing spreadsheets and email with an application and automated reporting.
- Experience with low-code application platforms such as Mendix used as an enterprise record system. Experience managing external development or systems integration partners against agreed scope, quality and cost.
- Background in manufacturing, supply chain, procurement or cost engineering, with an understanding of how productivity and savings translate into margin.
- Familiarity with continuous improvement methods such as Lean or Six Sigma.
- Experience operating machine learning models in production, including monitoring and retraining.
- Experience building a Center of Excellence or shared service function from an early stage
- Demonstrated ability to present to senior leadership and translate technical detail into business recommendations.
- Track record of developing engineers into more senior roles.
#LI-Hybrid
Skills Required
- 10-12 years experience in data engineering, analytics or data science
- Minimum 5 years directly leading technical teams including hiring and performance management
- Hands-on experience designing and operating production data pipelines on a cloud platform, including cost management
- Current working proficiency in SQL
- Current working proficiency in Python
- Experience building and deploying predictive models in production (classification, regression, gradient boosting, time-series forecasting) with validation and monitoring
- Experience designing and deploying data models or semantic layers with consistent definitions and dimensions
- Proven ability to diagnose underperforming business metrics, decompose causes, and present recommendations to senior leaders
- Experience owning recurring monthly or quarterly reporting cycles with reconciliation to Finance
- Fluency in English and Spanish, written and spoken
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The Company
