SHL’s recruitment portal shows an opening for Associate – Data Operations (VN1959). This role focuses on supporting large-scale data operations, evaluation workflows, and quality frameworks that power assessment and analytics platforms. It is well-suited for fresh graduates and early-career professionals who have strong attention to detail, analytical thinking, and an interest in working with structured data and evaluation systems. This blog provides a clear, career-oriented overview of the role, including responsibilities, required skills, career growth, and how to apply.
About the Role
The Associate – Data Operations position focuses on preparing, validating, and maintaining high-quality datasets used in assessments and machine learning-enabled systems. Associates work closely with defined guidelines and quality standards to ensure consistency, fairness, and accuracy across data outputs. The role involves analytical judgment, structured evaluation, and operational discipline rather than pure software development.
Role Overview
- Role: Associate – Data Operations (Job Code: VN1959)
- Company: SHL
- Location: Gurgaon, India
- Experience Level: Freshers / Entry-level
- Qualification: Bachelor’s Degree (B.E / B.Tech preferred)
- Employment Type: Full-time
- Domain: Data Operations / Analytics Support
This role offers a strong foundation for professionals aiming to grow into data analytics, data quality, or AI operations roles.
Purpose of the Associate – Data Operations Role
The primary purpose of this role is to ensure that data used across SHL’s assessment and analytics platforms is accurate, standardized, and reliable. Associates contribute directly to the quality of datasets that support evaluation systems and machine learning models. By following structured processes and applying analytical judgment, they help maintain fairness, consistency, and trust in data-driven outcomes.
Key Responsibilities
As an Associate – Data Operations in this role, you will typically:
- Collect, clean, and validate data to meet defined quality benchmarks
- Create standardized datasets for training and validating machine learning components
- Evaluate and grade candidate responses across video, audio, and written formats
- Apply structured evaluation frameworks consistently and accurately
- Develop and refine evaluation guidelines, prompts, and questions
- Track and plan data collection activities to meet timelines and targets
- Document processes, decisions, and results for quality assurance and audits
- Collaborate with internal teams to improve data quality and operational efficiency
These responsibilities ensure that data outputs are reliable, consistent, and aligned with business and assessment goals.
Technical and Analytical Skills Required
To succeed in this role, candidates generally need:
- Strong attention to detail and accuracy in data handling
- Basic understanding of data concepts and structured evaluation
- Comfort working with large datasets and repetitive quality checks
- Basic knowledge of SQL or databases (good to have)
- Logical and analytical thinking skills
- Ability to follow guidelines and standardized processes
- Clear written and verbal communication skills
Exposure to Python, data tools, or analytics concepts is an added advantage but not mandatory.
Professional and Soft Skills
In addition to analytical skills, the following professional competencies are important:
- Strong focus and consistency in task execution
- Ability to work independently with minimal supervision
- Time management and ownership mindset
- Adaptability to process-driven environments
- Willingness to learn and accept feedback
- Collaborative approach when working with cross-functional teams
These skills help associates perform effectively in structured, quality-driven roles.
Who Should Apply
This role is suitable for:
- Fresh graduates looking to start careers in data and analytics
- Candidates with an interest in data quality, evaluation, and operations
- Individuals who prefer structured, guideline-based work
- Graduates seeking exposure to machine learning support systems
- Early-career professionals aiming for long-term growth in data roles
A strong academic foundation and willingness to learn matter more than prior industry experience.
Work Culture and Environment
SHL promotes a professional, collaborative, and quality-focused work environment. Associates work within well-defined processes, quality benchmarks, and global standards. The culture emphasizes consistency, analytical thinking, and continuous improvement, with opportunities to learn from experienced professionals and work on globally used assessment platforms.
Career Progression
An Associate – Data Operations in this role can grow into:
- Senior Data Operations Analyst
- Data Quality Analyst
- Data Analyst / Business Analyst
- AI Operations or ML Support Specialist
- Process Excellence or Analytics Consulting Roles
Consistent performance, process improvement contributions, and domain expertise accelerate career growth.
How to Apply
Apply through the official Salesforce-hosted SHL recruitment page:
Enter your details carefully, upload an updated resume, and highlight skills related to data handling, analytical thinking, attention to detail, and structured work.
Preparing examples from academic projects, internships, or coursework related to data evaluation or analytics can strengthen your application and improve shortlisting chances.
