Wolters Kluwer is hiring for an FRESHER entry level Data Scientist / Data Analyst role in India

Position: Data Scientist (as per the JD, the role is more into Analytics)

Company: Wolters Kluwer

Location: Pune, India

Job type: Full-Time

Job mode: Hybrid (8 days onsite / month only)

Job requisition id: R0059235

Years of experience: 0 to 3 Years

Company description

• Wolters Kluwer stands as an expansive global leader delivering advanced cloud-based software, information, and AI-powered solutions to leading professionals around the world.

• Generating €6.1 billion in annual revenues, the company serves clients across more than 180 countries while maintaining operational hubs in over 40 global territories.

• Employing over 21,000 workforce members, the organization focuses on optimizing workflows, automating complex business routines, and increasing overall enterprise productivity.

• The company operates across high-stakes sectors where precision is vital, including healthcare, legal practice, corporate compliance, tax, finance, and specialized audit domains.

• Nearly 70 percent of digital revenues within the company originate directly from innovative AI-driven technology platforms designed to streamline intricate professional tasks.

• Carrying a operational history spanning nearly 190 years, the corporate structure continuously evolves its digital ecosystem to integrate cutting-edge artificial intelligence models.

• The organizational culture deeply emphasizes diversity, global equity, inclusive collaboration, and proactive employee well-being initiatives across all operational offices worldwide.

• Recognized widely in prestigious workplace rankings, the company fosters an environment driven by continuous growth, creative innovation, mutual respect, and meaningful societal impact.

Profile overview

• The Data Scientist position serves as an entry-level pathway designed to build a strong foundational expertise across operational data science methodologies.

• Candidates will focus heavily on performing essential core data manipulation procedures, supporting baseline analytical initiatives, and facilitating cross-functional research tasks across teams.

• The day-to-day responsibilities center around collecting, standardizing, and preprocessing structured datasets originating from diverse corporate operational repositories.

• New team members will actively participate in gathering raw inputs, validating information integrity, and executing basic data cleansing protocols to maintain dataset accuracy.

• The position requires conducting preliminary descriptive data analysis to generate initial business insights that support senior data engineering and modeling specialists.

• Professionals will assist in standard machine learning model training routines while receiving structured guidance from lead data science practitioners.

• Daily routines involve managing, maintaining, and organizing internal data repositories to ensure data assets remain accessible, reliable, and secure.

• Candidates will build introductory graphical visualizations and clear summary reports to effectively convey quantitative analytical findings to operational stakeholders.

• The position heavily involves direct collaboration with multidisciplinary peers to understand core analytical objectives, project parameters, and precise technical criteria.

• Continuous active learning is vital, requiring team members to track emerging market tools, algorithmic developments, and modern statistical methodologies.

• Thorough technical documentation of procedural data workflows, ingestion pipelines, and validation techniques forms a continuous requirement for the engineering process.

• The role directly upholds corporate data integrity initiatives, ensuring strict adherence to quality assurance standards and valid business metrics.

• Candidates must commit to strict authentic interview practices, demonstrating personal technical aptitude without relying on external generative artificial intelligence utilities.

• The operational setup operates under a hybrid working arrangement located in Pune, requiring candidates to attend office locations regularly per corporate guidelines.

Qualifications

• Demonstrable practical skill or academic knowledge concerning baseline data collection methodologies across multiple internal and external data source formats.

• Functional knowledge of core data cleaning procedures, preprocessing tools, and introductory feature preparation protocols needed for analytical processing.

• Proficiency in basic Python programming, focusing on data manipulation packages, numerical processing libraries, and basic script construction routines.

• Foundational understanding of Structured Query Language (SQL) concepts to effectively execute queries, retrieve specific parameters, and extract relational datasets.

• Strong capability in using Microsoft Excel tools to execute fundamental calculations, maintain data worksheets, and design simple business visualizations.

• Solid foundational knowledge surrounding introductory statistics, including descriptive measures, basic probability distributions, and elementary data interpretation techniques.

• Clear verbal and written communication abilities to translate fundamental numerical discoveries into straightforward, easy-to-understand executive summaries.

• Active team-player mindset with a strong interest in collaborative problem-solving, active listening, and continuous technical skill enhancement.

• Aptitude for structured documentation, demonstrating clear technical writing habits for tracking analytical processes, pipelines, and data validation rules.

• Familiarity with predictive modeling workflows, including supervised machine learning principles, model evaluation approaches, and basic algorithm concepts.

• Ability to work effectively within hybrid working setups, balancing individual home-office output with structured in-person collaborative sprint sessions.

• Analytical mindset focused on maintaining data accuracy, identifying pipeline anomalies, and resolving minor dataset discrepancies systematically and efficiently.

• Professional commitment to maintaining personal authenticity during technical evaluations, avoiding third-party automated response software or AI assistance platforms.

• Academic coursework or professional exposure related to computer science, quantitative analytics, information systems, statistics, engineering, or applied mathematics fields.

Additional info

• The recruitment framework mandates complete candidate transparency, strictly prohibiting the use of artificial intelligence generators or real-time digital assistants during assessments.

• Candidates must perform live interview interactions using standard natural presentation formats without virtual background filters to ensure recruitment integrity.

• Failure to adhere to authentic presentation rules or using third-party support options will result in direct disqualification from consideration.

• Physical in-person attendance at designated corporate offices may be integrated into final stage hiring routines per hiring manager discretion.

• The organization fosters an inclusive workforce environment supported by comprehensive global employee well-being programs and physical health resources.

• Recognized across top workplace industry awards, the firm actively encourages personal career progression, financial stability, and positive social impact.

• Equal employment opportunity standard policies apply across all application reviews without regard to race, gender, nationality, age, disability status, or background.

• Processing of candidate personal information aligns with strict international privacy directives, including global General Data Protection Regulation (GDPR) standards.

Please click here to apply.