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Data Scientist - (Senior Consultant to Manager) - EY Studio+ Jordan

EY

Data Scientist - (Senior Consultant to Manager) - EY Studio+ Jordan

EY

·

On-site

·

Full-time

·

3w ago

필수 스킬

Go

At EY, we’re all in shape to 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.

EY Studio+ brings together business, design and technology expertise to help organizations reimagine marketing, sales and customer experience. With a global network of 7,000 professionals across 50 countries, we deliver human‑centered, data‑driven solutions that fuel growth and create lasting impact.

We are expanding our fast‑growing EY Studio+ MENA team and are seeking talent across multiple skill sets. In these roles, you will help push the boundaries of design, innovation and development, working across industries to solve complex challenges using proven frameworks and methodologies. Join a global community shaping the future of business and technology.

The Opportunity

We are currently hiring for Data Scientists - (Senior Consultant to Manager level) to join our Commercial / Customer Value Creation Team.

About the Role:

We’re seeking an experienced data scientists to deliver insights and act as the hands‑on modeling lead on client engagements. You will “slice and dice” data using various methods and create new visions for the future. You’ll frame problems, engineer features, build and deploy models, and monitor them in production to support the customer value creation activities. You will ship models that run at scale, withstand audit, and clearly link to incremental business value. While mining, interpreting, and cleaning the data, you will be relied on to ask questions, connect the dots, and uncover hidden opportunities for realizing the data’s full potential. The ideal candidate will have mathematical and statistical expertise, extensive programming experience in multiple languages along with natural curiosity and a creative mind.

Core Responsibilities:

Problem Framing & Target Definition:

  • Translate commercial goals into modeling problems (e.g., churn, propensity‑to‑buy, uplift, LTV, survival/tenure) with clear success metrics and guardrails

  • Identify relevant data sources to mine for client business needs, and collect large structured and unstructured datasets and variables

  • Data Analysis:

  • Serve as data strategist to identify and integrate new datasets and execute analytical experiments to help solve problems across various domains and industries

  • Devise and utilize algorithms and models to mine data, perform data and error analysis to improve models, clean and validate data for uniformity and accuracy

  • Analyze data for trends and patterns, and interpret data with clear objectives in mind

  • Model Development:

  • Create reproducible pipelines and a feature registry to calculate model inputs

  • Develop and evaluate churn, cross/upsell propensity, uplift/treatment‑effect, LTV, ranking/NBA models and select algorithms fit for data, scale, and explainability

  • Use clear control/holdouts, quantify precision vs. recall, calibration, and profit curves, simulate outcomes and set practical thresholds and simple policies (eligibility, suppressions, frequency caps)

  • Operationalization:

  • Implement analytical models in production by collaborating with software developers and machine-learning engineers

  • Implement scoring and integrate outputs with client Mar Tech/decisioning for SMS, email, in‑app, IVR, and agent‑assist

  • Set up monitoring (performance, drift, calibration, data quality), alerting, and retrain cadence with rollback criteria

  • Governance, Risk & Explainability:

  • Produce model cards, document features/exclusions, and run proportionate explainability/fairness checks for regulated contexts and maintain audit‑ready artifacts

Enablement & Acceleration:

  • Create templates, reusable code, and quick‑start notebooks, /coach client analysts on model usage and monitoring

  • Contribute to practice POVs/case studies as needed

Qualification Requirements:

  • 3 to 6 years of hands-on experience in applied data science with proficiency in data mining, mathematics, and statistical analysis

  • Experience either in an in‑house data science role at a leading industry player or in a consulting company AI & Advanced Analytics team with multi‑industry exposure

  • Structured problem solver with strong client facilitation skills and executive storytelling ability (able to translate technical findings into clear commercial recommendations)

  • Advanced experience in pattern recognition and predictive modeling

  • Ability to work with multiple programming languages and datamining tools

  • Able to work effectively in a dynamic, research-oriented group that has several concurrent projects

  • Bachelor’s’ degree in the field of computer science is preferred (not mandatory)

Technical Expertise:

  • Data platforms: Azure Synapse/Databricks, Google Big Query, Snowflake, or Amazon Redshift

  • Languages: SQL, Python, R and SAS

  • BI/Reporting (any): Power BI, Tableau

What we look for

Highly motivated individuals with excellent problem-solving skills and the ability to prioritize shifting workloads in a rapidly changing industry. An effective communicator, you’ll be a confident team player that collaborates with people from various teams while looking to develop your career in a dynamic organization.

What we offer you

At EY, we’ll develop you with future-focused skills and equip you with world-class experiences. We’ll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more.

Are you ready to shape your future with confidence? Apply today.

To help create an equitable and inclusive experience during the recruitment process, please inform us as soon as possible about any disability-related adjustments or accommodations you may need.

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, 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+

직원 수

London

본사 위치

리뷰

3.4

10개 리뷰

워라밸

2.3

보상

3.7

문화

4.1

커리어

3.8

경영진

3.2

65%

친구에게 추천

장점

Good learning opportunities and career advancement

Supportive culture and kind people

Professional environment and good benefits

단점

Long working hours and poor work-life balance

Hectic and taxing work environment

Limited support for interns and technical growth

연봉 정보

31,254개 데이터

Mid/L4

Mid/L4 · Operations Research Analyst

1,738개 리포트

$142,571

총 연봉

기본급

$136,899

주식

-

보너스

$5,673

$100,128

$203,912

면접 경험

7개 면접

난이도

3.0

/ 5

소요 기간

14-28주

합격률

57%

면접 과정

1

Application Review

2

HR Screen

3

Hiring Manager Interview

4

Technical/Case Interview

5

Partner/Director Interview

6

Offer

자주 나오는 질문

Behavioral/STAR

Case Study

Technical Knowledge

Past Experience

Culture Fit