Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Leadership @ 4
Jira @ 4
Project Management @ 4
Observability @ 4
AI @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Bloomberg Data is responsible for acquiring, interpreting, and supplying the data that powers the Bloomberg Terminal and other products. The Data Management Lab (DML) within the Data organization promotes data discoverability, accessibility, interoperability, and analysis-readiness. The Process Engineering (PE) team, part of Quality Methods & Insights (QMI), supports design and optimization of operational processes across data manufacturing pipelines, partnering closely with Data Quality, Business Intelligence, and infrastructure engineers to improve observability, instrumentation, and analysis-readiness.
As Team Leader, you will manage a multi-disciplinary Process Engineering team (Industrial Engineers and Process Systems Specialists) and lead the strategic evolution from tactical implementation to strategic enablement. You will define strategy for analyzing, governing, and innovating within data manufacturing pipelines to deliver measurable business impact in product quality, operational efficiency, and risk management.
Responsibilities
- Set the strategic vision and roadmap for process excellence across data manufacturing pipelines.
- Build and manage a strategic portfolio of process improvement initiatives, prioritizing work that aligns with business goals (quality, efficiency, risk management).
- Lead, mentor, and develop a high-performing team of Industrial Engineers and Process Systems Specialists.
- Collaborate closely with Data Quality and Business Intelligence teams to integrate process initiatives with data quality and analytical goals.
- Oversee deep-dive investigations to identify systemic bottlenecks and inefficiencies and quantify opportunities using advanced IE/OR methodologies.
- Champion AI-driven automation and process redesign to reduce effort and improve outcomes.
- Drive prototyping, evaluation, and ROI measurement for novel solutions and tools before wider rollout.
- Establish process governance and knowledge transfer practices, and promote best practices for core workflow technologies (e.g., Jira).
- Interface with senior leadership across Data, Product, and Engineering to translate business needs into actionable process strategies.
Requirements
- Deep expertise in advanced quantitative process analysis and Operations Research methodologies (examples: simulation, optimisation, SPC, process mining).
- Proven track record leading analytical or technical projects that deliver measurable business impact (efficiency, quality, or risk management) from conception through completion.
- Exceptional strategic thinking, problem-solving, and stakeholder management skills; ability to influence senior leaders across a large organization.
- 8+ years of relevant professional experience, including 3+ years in a formal leadership or management role guiding technical or analytical teams.
- Advanced degree (MSc/PhD) in Industrial Engineering, Operations Research, Systems Engineering, or a related quantitative field.
Preferred (Nice-to-have)
- Experience in analytical, technical, or decision-science consulting (or internal consulting) focused on operational or systems-level transformation.
- Professional certification in process improvement (e.g., Lean Six Sigma Black Belt, CMQ/OE, TOC).
- Professional project management certification (e.g., PMP, PRINCE2, CSM).
- Experience applying IE/OR methodologies in complex operational environments (manufacturing, supply chain, logistics).
- Experience managing hybrid teams combining quantitative and systems-focused specialists.
- Strong understanding of modern data stacks and how to leverage them for operational monitoring and analysis.
Compensation & Benefits
- Salary Range: 135000 - 230000 USD annually (plus benefits and bonus).
- Bloomberg offers a comprehensive benefits plan that may include merit increases, incentive compensation (exempt roles), paid holidays, paid time off, medical, dental, vision, short and long term disability, 401(k) with match, life insurance, and wellness programs.
How to Apply
- Apply via the Bloomberg careers site.