Data Scientist (WFH)

About the role

This position is for a data scientist to help build an AI-driven B2B platform that delivers predictive results and practical business insights. The product mainly supports GCCs and Retail/CPG customers in the US market, with a focus on making organizations more AI-ready and future-ready.

You will be part of a high-performing data science function and work as an individual contributor, owning the development of production-ready methods and solutions while also handling the end-to-end DevOps lifecycle for machine learning models and data pipelines.

The role sits within a collaborative AI/ML environment that includes specialists in backend and frontend engineering, data modeling, machine learning, and LLMOps.

Key responsibilities

• Use statistical and analytical techniques to deliver accurate, high-quality model outputs.
• Create validation processes that compare model results against internal and external benchmarks.
• Work across supervised and unsupervised ML DevOps workflows.
• Apply advanced techniques for forecasting, causal analysis, price elasticity, churn prediction, anomaly detection, market matching, marketing mix modeling, segmentation, and store clustering.
• Contribute to solution development using Python, Java, or Scala.
• Work with container tools such as Docker and Kubernetes.
• Build and automate large-scale ETL pipelines and support agentic data enrichment.
• Handle data processing using tools like Apache Spark, Apache Beam, or Apache Flink.
• Work with data warehouse and lake systems such as Oracle Object Storage, Hadoop, Hive, Redshift, Azure Synapse, or PostgreSQL.
• Support embedded BI solutions.
• Apply strong knowledge of data structures and algorithms for scalable processing.
• Follow data governance, quality, and security best practices.
• Turn data into clear, actionable insights and communicate them effectively through storytelling.
• Track workflow performance and improve efficiency and accuracy.
• Resolve issues and enforce best practices around testing, version control, and reproducibility.
• Maintain detailed documentation for models, algorithms, deployment steps, and MLOps practices.
• Collaborate with cross-functional teams to deploy machine learning models into production.
• Partner with technology teams on AI platform development and implementation.

Eligibility

This opportunity is open only to candidates with at least 1 year of professional experience.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related discipline from a Tier 1 or Tier 2 accredited university.
• At least 4 years of hands-on experience in data science.
• Strong background in machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy.
• Exposure to cloud environments such as AWS, GCP, or Azure.
• Experience using visualization tools such as Oracle Analytics Cloud, Tableau, Power BI, or D3.js.
• Familiarity with platforms such as SageMaker, Vertex AI, Azure AI Foundry, or Databricks.
• Working knowledge of Elasticsearch, SQL, NoSQL, Apache Airflow, Apache Spark, Kafka, and MLflow.
• Hands-on experience with containerization, Kubernetes, CI/CD pipelines, and workflow orchestration tools.
• Comfort with agile ways of working and version control tools such as Git or Bitbucket.
• Proven progression in machine learning, data engineering, or a related role.
• Experience building and operationalizing both batch and real-time data pipelines at scale.

Additional details

This role is based in Hyderabad, Telangana, India, but is offered as work from home. The position is full-time and remote. Candidates should be able to start immediately. The application deadline is 3 July 2026 at 23:59:59. The hiring process includes 2 openings. The salary range is ₹12,00,000 to ₹33,00,000 per year. Perks include a 5-day work week and health insurance.

About the company

QuickHyre is an AI-powered hiring and job discovery platform that connects job seekers, recruiters, and educational institutions. The company uses advanced AI to improve job matching, resume screening, and virtual interview workflows.