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Senior Data Science Analyst

7 - 8 years

15 - 20 Lacs

Posted:2 days ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

    • Design, implement, and evaluate macroeconomic forecasting models, time series regressions, and machine learning models (including basic neural nets like RNN, LSTM architecture).
    • Apply and explain statistical concepts like regression, correlation, multicollinearity, stationarity, autocorrelation, and model assumptions to non-technical teams.
    • Work with time series, panel, and structured tabular data and perform feature engineering, data cleaning, and model validation.
    • Work with SQL to extract and manipulate data, perform preprocessing and feature engineering, tune models.
    • Work closely with business stakeholders, domain experts, and data engineers to define problems and deliver insights. Present insights and model performance clearly to technical and non-technical stakeholders
    • Optionally, experiment with deep learning or generative AI models for internal R&D use cases
Required Experience:
    • 7-8 years experience in Statistics, Machine Learning, Time Series modeling, and Python
Desired Skills:
    • Bachelor s or Master s in Statistics, Economics, Data Science, Computer Science, or a related field.
    • Strong command over Python (pandas, NumPy, scikit-learn, statsmodels) and SQL for data analysis, modeling, and manipulation.
    • Experience with real-world tabular datasets and business problem-solving
    • Strong applied knowledge of:
    • Supervised learning (linear/logistic regression, decision trees, ensemble models)
    • Unsupervised learning (K-means, DBSCAN, hierarchical clustering)
    • Evaluation metrics, cross-validation, feature importance
    • Solid grounding in Statistics
    • Probability distributions, statistical inference, hypothesis testing
    • Time Series modeling
    • Comfortable working with small datasets where feature engineering and domain understanding matter most.
    • Ability to explain complex concepts in simple terms and work effectively with both technical and non-technical stakeholders.

    • Nice to have skills:
    • Deep learning experience (e.g., PyTorch, TensorFlow)
    • Familiarity with version control (Git), dockers and AWS.
    • Exposure to GenAI concepts or LLM APIs (OpenAI, HuggingFace, LangChain)

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