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Risk Analytics- Process Mining - Digital Transformation and Analytics- Senior
·
On-site
·
Full-time
·
2w ago
At EY, we’re all in to shape your future with confidence.
We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.
Join EY and help to build a better working world.
Process Mining
- Digital Transformation and Analytics
Experience: 3–5 years
Role Summary
The Senior Analyst will support end-to-end process mining, ETL/data engineering, dashboarding, and process optimization initiatives across P2P, O2C, AP/AR, logistics, and operational processes. The role also expands to supporting automation (RPA), AI/ML‑led enhancements, and digital transformation activities.
Key Responsibilities
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Build and enhance process mining data models using Celonis, SAP Signavio, MPM/MPMx, including case creation, event logs, activity mapping, conformance checks, and KPI modelling.
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Design, transform, and optimize data pipelines using SQL, Python, ETL (Alteryx, Knime), SAP B1/SAP ECC).
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Develop front‑end process dashboards to track metrics such as cycle time, rework, GRN delays, invoice mismatches, AR aging, DSO, delivery delays etc.
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Support process optimization initiatives by conducting root-cause analysis, identifying bottlenecks/sources of inefficiency, and recommending corrective actions.
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Assist in digital transformation workstreams, RPA opportunity identification, automation workflows, predictive modelling, and AI/ML‑enabled insights.
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Support documentation creation: BPMN flows, TO‑BE designs, business requirements, UAT support, and process governance.
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Collaborate with cross‑functional teams (finance, supply chain, IT, operations) to drive timely completion of analytics deliverables.
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Participate in pre-sales support, value analysis, estimation, and business case preparation when needed.
Required Skills & Tools
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Process Mining: Celonis, Signavio, MPM/MPMx
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Data Engineering: SQL, Python, ETL tools (Knime, Alteryx), SAP data modelling
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Visualization: Tableau, Power BI, Qlik
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Automation: Exposure to RPA tools (UI Path, Automation Anywhere), ML-assisted solutions
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Process Documentation: BPMN, Visio, ARIS
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Domain Knowledge: P2P, O2C, AR/AP, logistics, telecom services, vendor management, ITSM
Preferred Experience
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Experience supporting digital transformation and operational excellence projects
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Working with RFP inputs, pre-sales decks, program documentation
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Predictive insights, automated notifications, and SLA monitoring
EY | Building a better working world
EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.
Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.
EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
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EYについて

EY
PublicEY, previously known as Ernst & Young, is a British multinational professional services network based in London, United Kingdom. Along with Deloitte, KPMG and PwC, it is one of the Big Four professional services firms.
10,001+
従業員数
London
本社所在地
レビュー
3.4
10件のレビュー
ワークライフバランス
2.3
報酬
3.7
企業文化
4.1
キャリア
3.8
経営陣
3.2
65%
友人に勧める
良い点
Good learning opportunities and career advancement
Supportive culture and kind people
Professional environment and good benefits
改善点
Long working hours and poor work-life balance
Hectic and taxing work environment
Limited support for interns and technical growth
給与レンジ
31,254件のデータ
Mid/L4
Mid/L4 · Operations Research Analyst
1,738件のレポート
$142,571
年収総額
基本給
$136,899
ストック
-
ボーナス
$5,673
$100,128
$203,912
面接体験
7件の面接
難易度
3.0
/ 5
期間
14-28週間
内定率
57%
面接プロセス
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
Technical/Case Interview
5
Partner/Director Interview
6
Offer
よくある質問
Behavioral/STAR
Case Study
Technical Knowledge
Past Experience
Culture Fit
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