- Develop statistical and machine learning models to solve business, product, and operational problems.
- Collect, clean, transform, analyze, and validate structured and unstructured datasets. Design experiments, select appropriate modeling approaches, evaluate model performance, and communicate findings clearly.
- Build scalable data and ML workflows using cloud platforms and managed machine learning services.
- Work with big data technologies such as Spark, Hadoop, and Databricks to process and analyze large datasets.
- Productionize machine learning models and contribute to reliable ML pipelines, deployment workflows, and monitoring.
- Apply MLOps practices including model versioning, experiment tracking, CI/CD for ML, reproducibility, and model monitoring.
- Create meaningful dashboards, reports, and visualizations that help stakeholders understand trends, model outcomes, and business performance.
- Explore and contribute to applications involving LLMs, generative AI, NLP, embeddings, and other modern AI techniques.
- Collaborate with engineering, product, business, and other stakeholders to convert ambiguous requirements into measurable data-driven solutions.
- Investigate model drift, data-quality issues, performance degradation, and production incidents, and implement improvements.
- Document methodologies, assumptions, experiments, model decisions, and results to support maintainability and knowledge sharing.
Required Qualifications
- Minimum 2 years of professional experience in Data Science, Machine Learning, Analytics, AI, or a closely related engineering role.
- Strong understanding of supervised and unsupervised machine learning, feature engineering, model evaluation, and statistical concepts.
- Experience with cloud platforms such as AWS, Azure, or GCP and their ML services, including SageMaker, Azure Machine Learning, or Vertex AI.
- Experience with big data technologies such as Apache Spark, Hadoop, or Databricks.
- Exposure to MLOps practices including model versioning, experiment tracking, CI/CD for ML, reproducibility, and monitoring tools such as MLflow.
- Experience with data visualization using Tableau, Power BI, or Python visualization libraries such as Matplotlib, Seaborn, or Plotly.
- Exposure to LLMs, generative AI, NLP applications, embeddings, or related modern AI technologies.
- Experience working in an Agile environment with cross-functional teams.
- Strong problem-solving, analytical, stakeholder-management, collaboration, and communication skills
Technical Skills & Competencies Area Expected Capability Programming & Analytics Machine Learning Cloud ML Big Data Strong Python skills and practical experience with SQL, data manipulation, statistical analysis, and ML libraries. Model development, feature engineering, validation, experimentation, model selection, evaluation, and optimization. AWS, Azure, or GCP with exposure to SageMaker, Azure ML, Vertex AI, or comparable managed ML services. Agile delivery, Git/version control, documentation, peer review, stakeholder communication, and iterative development. Spark, Hadoop, Databricks, distributed data processing, large-scale ETL/ELT, and data pipeline concepts. MLOps Visualization AI / NLP Ways of Working MLflow or equivalent tools, model registry/versioning, experiment tracking, CI/CD, deployment, monitoring, and reproducibility. Tableau, Power BI, Matplotlib, Seaborn, Plotly, or comparable data visualization technologies. LLMs, generative AI, NLP, embeddings, text analytics, prompt-based workflows, or related applications.
Pay: ₹2,000,000.00 - ₹2,500,000.00 per year
Benefits:
Ability to commute/relocate:
- Landran, Punjab 140307: Reliably commute or planning to relocate before starting work (Required)
Application Question(s):
- “Describe one Data Science/ML project you have personally taken from raw data to production. What was the business problem, which model/approach did you use, how did you evaluate it, and what measurable impact did it deliver?”
Experience:
- Data Scientist: 2 years (Required)
Language:
- Fluent English (Required)
Location:
- Landran, Punjab 140307 (Required)
Work Location: In person
