Datazymes

Management of Data Repository, HRMS Keka Handle Payroll Daily operational queries from employees Leave and Attendance Employee Engagement

3+ years of work experience in Python programming for AI/ML, deep learning, and Generative AI model development Proficiency in TensorFlow/PyTorch, Hugging Face Transformers and Langchain libraries Hands-on experience with NLP, LLM prompt design and fine-tuning, embeddings, vector databases and agentic frameworks Strong understanding of ML algorithms, probability and optimization techniques 6+ years of experience in deploying models with Docker, Kubernetes, and cloud services (AWS Bedrock, SageMaker, GCP Vertex AI) through APIs, and using MLOps and CI/CD pipelines Familiarity with retrieval-augmented generation (RAG), cache-augmented generation (CAG), retrieval-integrated generation (RIG), low-rank adaptation (LoRA) fine-tuning Ability to write scalable, production-ready ML code and optimized model inference Experience with developing ML pipelines for text classification, summarization and chat agents Prior experience with SQL and noSQL databases, and Snowflake/Databricks

As a data professional at DataZymes Analytics, you will be involved in setting up data pipelines in Azure, utilizing Azure Data Factory, and configuring Azure Data Lake with both structured and unstructured data. Your role will require you to be a self-starter who can independently design, develop, and deliver solutions efficiently. Your responsibilities will also include demonstrating a strong understanding of Azure services such as Azure Storage (AFS, Blob, Data Lake) and Azure Functions. Additionally, you should possess a solid knowledge of databases, enabling you to write complex queries and design schemas effectively. Your expertise in setting up CI/CD pipelines in Azure through GitHub will be crucial for ensuring seamless development processes. To excel in this role, you should hold a Bachelor's or Master's degree in Computer Science or Information Technology. Experience with batch job scheduling, identifying data or job dependencies, and proficiency in data warehousing, ETL, and big data processing will be advantageous. While familiarity with the Pharma domain is preferred, it is not mandatory. At DataZymes Analytics, we value accuracy, efficiency, and innovation. By leveraging the latest technologies and best practices, we aim to deliver high-quality solutions with fast turnaround times. If you are passionate about data analytics and are eager to contribute to a dynamic team that thrives on excellence, we welcome you to apply and join us on our journey of transforming data into actionable insights for our Life Sciences clients.,

You will be responsible for HR Data Management by maintaining and updating employee records in our HR information systems with precision and confidentiality. This includes handling onboarding, offboarding, and other daily HR transactions efficiently. Additionally, you will act as the main point of contact for employees and managers, addressing inquiries related to HR policies, benefits, and general HR processes to ensure a positive employee experience. Your role will involve assisting in administering employee benefits programs, such as health insurance, retirement plans, and additional perks. You will also manage various leave programs, ensuring compliance with local regulations and company policies. Furthermore, you will be responsible for preparing regular HR reports and analytics on key metrics to help identify trends for process improvement. Collaboration with external HR service providers to ensure seamless service delivery will be part of your responsibilities. It is essential to stay updated on HR regulations and employment laws relevant to startups and assist in maintaining HR policies and procedures to ensure compliance and policy adherence. To qualify for this role, you must have a Bachelor's or Master's degree in Human Resources, Business Administration, or a related field. A minimum of 2-5 years of experience in HR operations or related roles within a startup environment is required. Strong attention to detail and the ability to handle HR data accurately and efficiently will be crucial for success in this position.,