Data Scientist

2 days ago


India Futurism Full time

ID: 816 | 5-7 yrs | India | careers**Job Title**:Data Scientist

**Job Location**:Hinjewadi Phase 1, Pune

**Experience**:5 to 7 Years

**Shift**: 1.00-10.00 PM IST: Monday to Friday

**Qualification**:BE, B. Tech

**Skills & Responsibilities**

Data Analysis & Preprocessing:

- Collect, clean, and analyze large structured/unstructured datasets from various sources.
- Perform feature engineering, outlier detection, and dimensionality reduction to improve model accuracy.

Machine Learning Model Development:

- Develop and optimize ML models for classification, regression, clustering, and recommendation systems.
- Implement deep learning architectures using TensorFlow, PyTorch, or Scikit-learn.
- Perform hyperparameter tuning, model evaluation, and explainability analysis.

AI/ML Deployment & MLOps:

- Build scalable ML pipelines and deploy models using AWS SageMaker, Google Vertex AI, or Azure ML.
- Optimize models for real-time inference and batch processing.
- Work with MLOps tools (Kubeflow, MLflow, Airflow, Docker, Kubernetes) to automate training and monitoring.

Business Intelligence & Insights:

- Collaborate with cross-functional teams (engineering, product, and business teams) to translate insights into actionable business strategies.
- Develop interactive dashboards (Tableau, Power BI, Streamlit) for real-time data visualization.

Research & Innovation:

- Stay up to date with the latest advancements in AI, NLP, and deep learning.
- Experiment with LLMs (Large Language Models), Generative AI, RAG-based search, and Transformers to enhance AI capabilities.

Must have Skills:

- Machine Learning & Deep Learning: Regression, Classification, Clustering, CNNs, RNNs, LSTMs
- Programming Languages: Python, R, SQL
- ML Frameworks: TensorFlow, PyTorch, Scikit-learn, XGBoost
- Data Visualization: Matplotlib, Seaborn, Plotly, Tableau, Power BI
- NLP & Generative AI (Bonus): Transformers, OpenAI, BERT, GPT, RAG-based search

Nice to have Skills:
Big Data & Cloud: Spark, Snowflake, AWS, Google Cloud, Azure

MLOps & Model Deployment: Docker, Kubernetes, MLflow, Airflow, FastAPI


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