HR Executive

It is expected to be a data driven HR executive with an AI first mindset. 1. Recruitment Support Source and screen candidates for various roles across departments. Coordinate interview scheduling and feedback loops between candidates and hiring managers. Facilitate smooth onboarding of selected candidates, including documentation and induction support. 2. Employee Lifecycle Coordination Maintain up-to-date employee files and records in both digital and physical formats. Support activities related to joining formalities, confirmation processes, and exit management. Keep HRIS data accurate, including attendance, leave records, and employment history. 3. HR Operations Manage day-to-day operational queries regarding leave, attendance, and other HR processes. Liaise with internal teams to gather and update necessary HR information. Ensure HR processes are well-documented and audit-ready. 4. Employee Engagement Assist in planning and executing employee engagement activities such as Fun Fridays, birthday celebrations, and festivals. Gather feedback and suggest improvements to engagement strategies. 5. Hiring Coordination Support sourcing and onboarding of instructors and associates in DataCouch and its partners. Ensure documentation and time-zone based coordination for global hires is handled smoothly. 6. Administration & Coordination Assist with basic administrative functions including asset tracking, vendor follow-up, and petty cash management (where applicable). Review of Juniors Tasks Pantry Inventory Management Ensuring office cleanliness Ensure timely coordination and communication to resolve administrative tasks. Requirements Bachelors degree in Human Resources, Business Administration, or a related field Experience in recruitment, onboarding, and HR operations preferred Strong communication and interpersonal skills Good organizational and time-management abilities Attention to detail and documentation accuracy Proficiency in MS Office / Google Workspace

1-3 years
Educational Background: Bachelor's and Master’s degrees in Data Science, Computer Science, Statistics, or a related field. Technical Skills: Proficient in Python and familiar with key data science libraries (Pandas, Scikit-Learn, TensorFlow, or PyTorch). Strong understanding of all complex machine learning algorithms not limited to decision trees, random forests, and gradient boosting machines. Competence in data preprocessing, cleaning, and analysis. Familiarity with data cleaning, transformation, and preprocessing techniques. Experience with SQL and possibly some NoSQL databases for data querying and manipulation. Basic knowledge of data visualization tools like Matplotlib and Seaborn. Strong skills in SQL for data extraction, and the ability to work with complex database systems. Advanced knowledge of analytical tools and software such as Excel, Tableau, or more specialized software depending on the industry (e.g., SAS, SPSS). Experience with data visualization and the ability to create interactive dashboards. Vast knowledge of NLP, Deep Learning, Machine Learning , Knowledge of genAI with implementation knowledge (LLM, fine tuning RAG implementation) and many more. Familiarity with cloud services (AWS, Azure, Google Cloud) for data processing and storage.. Professional Experience: 2-3 years of experience in a data science or related role. Proven track record of developing and deploying machine learning models to solve business problems. Experience in projects that involve complex data structures and large-scale datasets. Exposure to model validation and implementation in a production environment. Demonstrated experience in analyzing large datasets and delivering actionable insights. Proven track record of effectively communicating findings to help inform business decisions. Experience in performing statistical analysis, forecasting, and establishing data structures that optimize analytical capabilities. Soft Skills: Strong problem-solving skills with a capability to work through complex issues using a logical and analytical approach. Good communication skills to effectively articulate insights and technical details to non-technical stakeholders. Ability to work collaboratively in team settings and manage project timelines effectively. Strong attention to detail with the capability to work on multiple projects simultaneously. Effective communication skills, capable of presenting complex information in an understandable and compelling manner. Collaboration skills to work effectively with both technical teams and business units.