Data Scientist (WFH)

About the job:
We are an agentic Data Science B2B platform focused on delivering predictive outcomes and actionable insights. Primarily serving GCCs and Retail/CPG clients in the US market, we are reimagining data science and enabling organizations to become AI- and future-ready.

We are seeking a high-performing individual contributor on the Data Science team to support the development of production-grade methodologies and solutions, while managing the full lifecycle of DevOps for machine learning models and data pipelines on the platform.

You will work closely in a cross-functional, world-class AI/ML team comprising experts in backend and frontend engineering, data modeling, ML, and LLMOps.

Key Responsibilities:

A. Method Application

1. Apply and integrate various statistical and analytical methods, ensuring high rigor and accuracy in model outcomes

2. Build processes to compare model outputs with internal and external benchmarks for validation and reliability

3. Demonstrate strong experience in ML DevOps across supervised and unsupervised learning methods

4. Apply advanced methods in areas such as univariate forecasting, causal forecasting, price elasticity modeling, customer churn, anomaly detection, market matching, marketing mix modeling, customer segmentation, and store clustering

5. Experience in Retail, CPG, or Manufacturing domains is desirable

B. Solution Engineering

1. Strong programming skills in Python, Java, or Scala

2. Experience with containerization technologies such as Docker and Kubernetes

C. Data ETL

1. Experience working with datasets such as Scintilla, Nielsen, Circana, and Retail Media Network

2. Build and automate ETL pipelines capable of handling large-scale data and enabling agentic data enrichment

3. Expertise in data processing tools such as Apache Spark, Apache Beam, or Apache Flink

4. Experience with data warehousing and data lake technologies such as Oracle Object Storage, Apache Hadoop, Apache Hive, Amazon Redshift, Azure Synapse, or PostgreSQL

5. Ability to work with embedded BI solutions

6. Strong understanding of data structures and algorithms for scalable data processing systems

7. Strong knowledge of data governance, data quality, and data security principles

D. Data Storytelling

1. Translate data into actionable insights

2. Effectively communicate findings through data storytelling

E. Workflow Improvements and Monitoring

1. Monitor performance of data science workflows and optimize for efficiency and accuracy

2. Troubleshoot issues and implement best practices such as unit testing, version control, and reproducibility

3. Develop and maintain comprehensive documentation for models, algorithms, and deployment processes

4. Maintain knowledge base, including MLOps processes and best practices

5. Collaborate with cross-functional teams to deploy and integrate machine learning models into production systems

6. Work closely with technology teams for AI platform development and implementation

Who can apply:

Only those candidates can apply who:
- have minimum 1 years of experience

Salary:
₹ 12,00,000 - 33,00,000 /year

Experience:
1 year(s)

Deadline:
2026-11-07 23:59:59

Other perks:
5 days a week, Health Insurance

Skills required:
Python, SQL, Machine Learning, Data Science and Natural Language Processing (NLP)

Other Requirements:
- 1. Bachelor’s degree in Computer Science, Engineering, or a related field from a Tier 1 or Tier 2 accredited university
- 2. 4+ years of hands-on experience in the data science domain
- 3. Experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy
- 4. Experience with cloud platforms such as AWS, GCP, or Azure
- 5. Experience with data visualization tools such as Oracle Analytics Cloud, Tableau, Power BI, or D3.js
- 6. Experience with platforms such as SageMaker, Vertex AI, Azure AI Foundry, or Databricks
- 7. Working knowledge of Elasticsearch, SQL, NoSQL, Apache Airflow, Apache Spark, Kafka, and MLflow
- 8. Experience with containerization, Kubernetes, CI/CD pipelines, and workflow orchestration tools
- 9. Familiarity with agile methodologies and version control systems such as Git or Bitbucket
- 10. Proven progressive experience in machine learning, data engineering, or similar roles
- 11. Experience in building and operationalizing large-scale batch and real-time data pipelines

About Company:
QuickHyre is an AI-powered job hiring and finding platform that bridges the gap between job seekers, recruiters, and educational institutions. We leverage cutting-edge AI technology to streamline recruitment processes, making job matching, resume screening, and virtual interviews more efficient.