Data Scientist- Gen AI- 5+years- Gurgaon (Hybrid)

5 - 9 years

20 - 35 Lacs

Posted:2 days ago| Platform: Naukri logo

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Work Mode

Hybrid

Job Type

Full Time

Job Description

We are looking for an experienced Data Scientist who is passionate about uncovering insights from data and delivering scalable data-driven solutions. The ideal candidate will have a strong foundation in machine learning, statistics, and programming, and will play a critical role in transforming complex datasets into actionable intelligence.

Key Responsibilities:

  • Design and implement machine learning models and data science solutions for predictive analytics, classification, and clustering problems.
  • Collaborate with data engineers and software developers to deploy ML models in production environments.
  • Conduct data wrangling, exploratory data analysis (EDA), and data visualization to identify trends and patterns.
  • Build data pipelines and workflows using Python, SQL, or cloud technologies (e.g., AWS, Azure, GCP).
  • Leverage large datasets from internal and external sources to create advanced analytics models.
  • Communicate findings effectively to both technical and non-technical stakeholders.

Key Skills / Keywords:

  • Machine Learning
  • Data Science
  • Data Developer
  • Statistical Analysis
  • Data Mining
  • Python / R
  • SQL / NoSQL
  • Big Data (Hadoop, Spark)
  • Data Visualization (Power BI,Tableau, matplotlib, seaborn)
  • Natural Language Processing (NLP)
  • Deep Learning (TensorFlow,PyTorch)
  • Cloud Platforms (AWS, Azure,GCP)
  • Model Deployment
  • Version Control (Git)
  • CI/CD for ML

Qualifications:

  • Bachelors or master’s degree in computer science, Data Science, Statistics, Mathematics, or a related field.
  • 3+ years of experience as a Data Scientist, ML Engineer, or Data Developer.
  • Demonstrated success in building and deploying ML models.

Preferred Attributes:

  • Knowledge of MLOps, Kubeflow,or MLFlow.
  • Experience with time series forecasting, recommendation engines, or anomaly detection.
  • Contributions to open-source or published papers in data science journals.

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