Position: Associate Data Scientist
Company: TriNet
Location: Hyderabad, Telangana, India
Job type: Full-time
Job mode: Onsite (100% in office)
Job requisition id: 3004076
Years of experience: 0–3 year (Freshers eligible)
Company Description
TriNet stands as a premier provider of comprehensive, full-service human resources solutions tailored specifically for small to midsize businesses across various commercial sectors.
The organisation empowers client productivity by enabling companies to outsource critical HR functions to a single, highly reliable strategic business partner.
Core product capabilities cover broad operational scopes including automated payroll processing, human capital strategic consulting, employment law compliance management, and complete risk management frameworks.
Additional core services encompass workers' compensation insurance along with extensive employee benefits administration such as group health coverage and structured retirement plans.
Headquartered in the United States, the enterprise maintains a robust nationwide presence and trades publicly on the New York Stock Exchange under the stock ticker symbol TNET.
The company's dedicated global workforce leverages state-of-the-art cloud platforms and data infrastructure to power client growth and streamline administrative operations.
Through ongoing technological transformation and data-driven insights, the company enables growing enterprises to focus entirely on their primary commercial offerings and strategic expansions.
Employees benefit from a progressive corporate cultural environment that emphasizes innovation, operational accountability, inclusive practices, and sustained personal professional growth.
Profile Overview
The Associate Data Scientist serves as an integral core contributor within the dedicated Enterprise Data and Analytics organizational division.
The primary mission involves applying structured mathematical, technical, and analytical methodology to solve well-defined business and data engineering problems.
Daily operations center on supporting senior data scientists, principal engineers, and cross-functional teams in constructing, validating, and deploying analytics platforms.
Core tasks demand the execution of disciplined data transformation workflows, thorough statistical testing, and accurate predictive model construction.
Practitioners utilize fundamental machine learning methodologies including linear and non-linear regression techniques, statistical classification models, clustering algorithms, and predictive time-series forecasting.
The position prioritizes extreme technical precision, operational consistency, and systematic model verification against established business requirements.
Team members perform exhaustive exploratory data analysis to isolate hidden patterns, underlying trends, operational anomalies, and systematic data quality defects.
Early-stage workflows entail rigorous data preprocessing, complex feature engineering execution, feature selection, and comprehensive data readiness validation.
Emerging technical domain involvement includes exposure to unstructured datasets, modern Natural Language Processing approaches, and Large Language Model architectures.
Hands-on tasks involve experimenting with prompt performance, executing system outputs validation, and conducting detailed benchmarking tests for artificial intelligence components.
Success within the post requires strict adherence to corporate software development guidelines, version control practices, and detailed model documentation.
The position offers a foundational career platform designed to build deep expertise in quantitative analytics, machine learning operations, and enterprise data strategy.
Qualifications
Completion of a formal Bachelor’s Degree in Data Science, Statistics, Mathematics, Computer Science, Quantitative Economics, or a closely related quantitative academic discipline.
Demonstrable practical experience spanning zero to one year, with fresh university graduates and recent academic degree completers explicitly encouraged to submit applications.
Prior exposure to practical analytics projects or completed internship programs within data science, software engineering, or quantitative research domain is highly advantageous.
Proven foundational programming capability using analytical coding languages such as Python, R, or equivalent statistical software packages.
Basic understanding of quantitative statistical methods, mathematical probability concepts, linear algebra fundamentals, and foundational machine learning framework architectures.
High degree of practical precision, sharp analytical attention to detail, and a rigorous commitment to absolute numerical accuracy across deliverable outputs.
Systematic problem-solving approach equipped with strong foundational reasoning abilities to navigate complex quantitative tasks logically.
Conceptual knowledge covering model performance evaluation criteria, validation matrices, confusion matrix analysis, cross-validation methods, and model output interpretation principles.
Operational familiarity with statistical hypothesis testing protocols, data transformation routines, exploratory analysis workflows, and data visual representation formats.
Clear understanding of core software engineering practices, basic computational algorithm design, and structured database querying environments.
Complete alignment with professional integrity, personal accountability, code quality guidelines, and high corporate ethical conduct standards.
Excellent interpersonal communication capabilities required to collaborate efficiently within multi-disciplinary technical teams and accurately document developmental pipelines.
Additional Info
Employees work on-site within a pleasant, clean, modern, and ergonomic professional corporate office installation situated in Hyderabad.
Daily physical attendance is mandatory as the role is established as a fully in-office assignment operating at 100% office presence.
Travel responsibilities associated with the operational function remain minimal to non-existent under standard corporate operating circumstances.
Comprehensive employee benefits packages include extensive health, dental, and vision insurance plan coverages for eligible staff members.
Financial planning offerings feature retirement investment plans alongside direct participation opportunities in the corporate Employee Stock Purchase Plan.
Paid time off structures grant twelve annual paid or floating corporate holidays, general accrued leave allocations, and dedicated volunteer leave hours.
Comprehensive family support initiatives include generous paid parental leave benefits along with paid time off reserved for family care and personal health recovery.
Staff members gain entry to corporate educational assistance programs designed to sponsor ongoing skill acquisition, certification courses, and professional development.
Exclusive merchant discounts and cost-saving opportunities are made available across numerous commercial vendors via the internal employee marketplace platform.
The enterprise maintains strict compliance as an Equal Opportunity Employer, maintaining unbiased hiring protocols across protected demographic classifications.
Comprehensive reasonable physical and technical accommodation procedures are actively maintained to assist candidates operating with documented physical or mental disabilities.
Corporate policy reserves complete rights to adjust, update, or reorganize operational responsibilities and project assignments based on evolving market and enterprise demands.
Please click here to apply.
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