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Data Management (Data Scientist) 

The opportunity

EY's global enterprise technology group provides various enabling services (ERP, infrastructure, platforms, service desk) to assist over 300K employees in creating and delivering solutions and services to Fortune 500, privately held and government-like entities.

The Data Scientist will be responsible for leveraging the data lake to drive advanced analytics and predictive modelling initiatives. This role requires a combination of statistical expertise, machine learning knowledge, and the ability to derive insights from large volumes of complex data. The Data Scientist will work closely with business stakeholders to understand their challenges and develop data-driven solutions.

Key responsibilities

• Develop and implement machine learning models and algorithms to analyze large datasets within the data lake.
• Collaborate with business stakeholders to identify opportunities for leveraging data to drive business solutions.
• Perform exploratory data analysis to understand underlying patterns, correlations, and trends.
• Design and execute experiments to test hypotheses and validate data-driven insights.
• Create predictive models for forecasting, classification, clustering, and optimization problems.
• Interpret and communicate findings to technical and non-technical audiences through clear visualizations and reports.
• Integrate advanced analytics into end-user applications and business processes.
• Maintain up-to-date knowledge of data science techniques, tools, and best practices.
• Mentor junior data scientists and analysts, and contribute to the team's skill development.
• Ensure adherence to data privacy and security guidelines when handling sensitive information.

Skills and attributes for success

• A self-starter, independent-thinker, curious and creative person with ambition and passion. This individual should possess a combination of technical skills, analytical abilities, and leadership attributes

To qualify for the role you must have 

• Relevant Experience: 3-4 years of experience in a data science role, with a proven track record of developing and deploying machine learning models.
• Machine Learning: Strong understanding of machine learning techniques and algorithms, such as regression, classification, clustering, neural networks, and natural language processing.
• Programming Languages: Proficiency in programming languages commonly used in data science, such as Python, R, or Scala.
• Data Analysis Tools: Experience with data analysis and visualization tools/libraries like Pandas, Matplotlib, Seaborn, or equivalent.
• Big Data Technologies: Familiarity with big data technologies and frameworks such as Hadoop, Spark, or Databricks.
• Statistical Analysis: Solid foundation in statistical analysis and the ability to apply statistical methods to solve real-world problems.
• Data Wrangling: Skills in data preprocessing, cleaning, and wrangling to prepare data for analysis.
• Deep Learning: Knowledge of deep learning frameworks like TensorFlow or PyTorch is a plus.
• Collaboration and Communication: Ability to work effectively in a team environment and communicate complex concepts to non-technical stakeholders.
• Problem-Solving: Excellent problem-solving skills with the ability to think critically and creatively in a data-driven approach.
• Version Control and Collaboration Tools: Familiarity with version control systems like Git and collaboration tools such as Jupyter Notebooks or Databricks notebooks.

Ideally, you'll also have

What we look for

• Bachelor's degree in Data Science, Computer Science, Statistics, or a related field.
• Data science or any other relevant certification is preferred
• PowerBI or any other reporting platform experience is a must 
• Knowledge on Power Automate, Qlik View , or any other reporting platform is an added advantage 
• IT IL Foundation certification is preferred

What we offer

As part of this role, you'll work in a highly integrated, global team with the opportunity and tools to grow, develop and drive your career forward. Here, you can combine global opportunity with flexible working. The EY benefits package goes above and beyond too, focusing on your physical, emotional, financial and social well-being. Your recruiter can talk to you about the benefits available in your country. Here's a snapshot of what we offer: 

• Continuous learning:  You'll develop the mindset and skills to navigate whatever comes next.
• Success as defined by you:  We'll provide the tools and flexibility, so you can make a meaningful impact, your way.
• Transformative leadership:  We'll give you the insights, coaching and confidence to be the leader the world needs.
• Diverse and inclusive culture:  You'll be embraced for who you are and empowered to use your voice to help others find theirs.

Azure developer : Position : Offshore Experience Level: 8-10 yearsKey Responsibilities & Requirements:1. Hands-on experience with Microsoft Fabric, including Lakehouse, Data Factory, and Synapse.2. Strong expertise in PySpark and Python for large-scale data processing and transformation.3. Deep knowledge of Azure data services (ADLS Gen2, Azure Databricks, Synapse, ADF, Azure SQL, etc.).4. Experience in designing, implementing, and optimizing end-to-end data pipelines on Azure.5. Understanding of Azure infrastructure setup (networking, security, and access management) is good to have.6. Healthcare domain knowledge is a plus but not mandatory. domain knowledge is a plus but not mandatory.

Role Description:

We are seeking an experienced Data Management Expert with expertise in Enterprise Data Management (EDM), Master Data Governance, and Data Quality to support the design and implementation of a Comprehensive EDM Framework. The role requires deep expertise in master data management (MDM), data governance, cleansing, enrichment, migration, and process automation across ERP systems like SAP ECC/S4HANA and other enterprise platforms.

Key Responsibilities:

• Develop and implement EDM frameworks based on DAMA, CMMI, DCAM, and industry best practices.
• Conduct data maturity assessments to evaluate the current state and identify improvement areas.
• Define master data governance policies and implement data standards for Vendor Master, Customer Master, Material Master, and Pricing Master data.
• Establish and manage data quality frameworks, including profiling, cleansing, enrichment, deduplication, and validation techniques to ensure accuracy.
• Implement metadata management strategies, including metamodels, data catalogs, lineage tracking, and glossaries.
• Develop and maintain data models (conceptual, logical, and physical) for enterprise-wide data consistency.
• Define and monitor KPIs for data quality, ensuring compliance with business and regulatory standards.
• Collaborate with cross-functional teams (IT, finance, procurement, operations) to align data management objectives.
• Lead tool evaluations for data governance, MDM, metadata, and lineage platforms.
• Assist in automating manual data processes and workflows, enhancing operational efficiency and reducing errors.
• Experience in setting up and operationalization of a centralized Data Management Office (DMO).

Key Tools & Technologies:

• ERP : SAP ECC/S4HANA
• Data Governance, Metadata & Quality Tools: Informatica, Talend, Alation, MS Purview, Collibra, Axon etc (exp of one of the tools is required, collibra preferred)
• BI & Analytics: Power BI, Snowflake, Azure, Hive (not mandatory)
• Data Integration & ETL: APIs, middleware, data lakes, ETL tools. (preferred)

Preferred Qualifications:

• Education: Bachelor’s/Master’s degree in Computer Science, Information Systems, Data Management, or a related field.
• Certifications: Certified Data Management Professional (CDMP), SAP MDG certification, Lean Six Sigma (preferred).

Experience:

• 5 to 12 years in enterprise data management, data governance, and MDM.
• Industry/consulting experience working with supply chain, procurement, finance, and vendor/customer data management domains is a plus.

Industry

• Preferred industry experience – Banking and Financial Services

DGO/Master Data Steward/Master Data Management

Work Location: Manyata Tech Park, Bangalore

Shift Timing: Rotational Shifts

Exp: 1 to 5 yrs

SAP Exp is a must

Job Description:

· Create and maintain master data attributes for customers, suppliers, parts, solutions, and items.

· Work as part of the Master Data Governance team to recommended changes to improve process efficiencies, ensuring timely and professionally communication to users, management, and senior leadership with repetitive issues

· Interface with cross-functional teams to validate adherence to master data policies and correct non-adherence where appropriate

· Perform validation and corrections via audit reports to ensure standardization daily

· Application of best business practices for mass data updates as appropriate

· Serve as a subject matter expert (SME) in the DGO operations

· Develop standard procedures, user guides and other necessary training and job aid materials, along with provide training as needed

· Utilize analytical skills to identify trends

· Performs other duties as assigned based on business needs.

· Becomes a Change Ambassador, promoting and ensuring adoption of new processes or implementations across Black Box.

· Ensure that only approved and valid changes are allowed into a production environment

Education/Experience Requirements

· Bachelor’s Degree in related fields or related experience, preferred

· 3 years relevant experience in data management and analysis or other related fields

· Prefer knowledge of SAP Item Master Data Management

· Experience with computer system validation and validated testing is a plus

· Experience in working with an ERP Master Data Add, Changes, Deletes

Interested individuals can share resume to

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Role Description:

We are seeking an experienced Data Management Expert with expertise in Enterprise Data Management (EDM), Master Data Governance, and Data Quality to support the design and implementation of a Comprehensive EDM Framework. The role requires deep expertise in master data management (MDM), data governance, cleansing, enrichment, migration, and process automation across ERP systems like SAP ECC/S4HANA and other enterprise platforms.

Key Responsibilities:

• Develop and implement EDM frameworks based on DAMA, CMMI, DCAM, and industry best practices.
• Conduct data maturity assessments to evaluate the current state and identify improvement areas.
• Define master data governance policies and implement data standards for Vendor Master, Customer Master, Material Master, and Pricing Master data.
• Establish and manage data quality frameworks, including profiling, cleansing, enrichment, deduplication, and validation techniques to ensure accuracy.
• Implement metadata management strategies, including metamodels, data catalogs, lineage tracking, and glossaries.
• Develop and maintain data models (conceptual, logical, and physical) for enterprise-wide data consistency.
• Define and monitor KPIs for data quality, ensuring compliance with business and regulatory standards.
• Collaborate with cross-functional teams (IT, finance, procurement, operations) to align data management objectives.
• Lead tool evaluations for data governance, MDM, metadata, and lineage platforms.
• Assist in automating manual data processes and workflows, enhancing operational efficiency and reducing errors.
• Experience in setting up and operationalization of a centralized Data Management Office (DMO).

Key Tools & Technologies:

• ERP : SAP ECC/S4HANA
• Data Governance, Metadata & Quality Tools: Informatica, Talend, Alation, MS Purview, Collibra, Axon etc (exp of one of the tools is required, collibra preferred)
• BI & Analytics: Power BI, Snowflake, Azure, Hive (not mandatory)
• Data Integration & ETL: APIs, middleware, data lakes, ETL tools. (preferred)

Preferred Qualifications:

• Education: Bachelor’s/Master’s degree in Computer Science, Information Systems, Data Management, or a related field.
• Certifications: Certified Data Management Professional (CDMP), SAP MDG certification, Lean Six Sigma (preferred).

Experience:

• 5 to 12 years in enterprise data management, data governance, and MDM.
• Industry/consulting experience working with supply chain, procurement, finance, and vendor/customer data management domains is a plus.

Industry

• Preferred industry experience – Banking and Financial Services