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Providence Global Center
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Senior Data Scientist

Senior Data Scientist

Providence Global Center

3 - 5 years

30 - 35 Lacs

hyderabad

Posted:1 day ago| Platform:

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Skills Required

deep learning data science time series analysis analytical machine learning healthcare pwd big data python

Work Mode

Work from Office

Job Type

Full Time

Job Description

We are seeking a highly skilled and experienced

Senior Data Scientist

with deep expertise in

statistical modeling, machine learning

, and data-driven decision-making. The ideal candidate will lead complex analytical projects, design robust predictive models, and collaborate cross-functionally to drive strategic insights and innovation.

Key Responsibilities:

Lead end-to-end data science projects from problem definition to model deployment.
Apply advanced statistical techniques (e. g. , hypothesis testing, Bayesian inference, time series analysis) to solve business problems.
Design, build, and validate machine learning models for classification, regression, clustering, and recommendation systems.
Interpret model results and communicate findings to stakeholders with clarity and impact.
Collaborate with data engineers to ensure scalable data pipelines and model integration.
Mentor junior data scientists and contribute to best practices in model development and evaluation.
Stay current with the latest research and trends in ML/AI and apply them to real-world problems.

Required Qualifications:

masters or Ph. D. in Statistics, Mathematics, Computer Science, or a related field.
3-5+ years of experience in data science, with a strong portfolio of statistical and ML projects.
Proficiency in Python or R, and ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
Good Understanding in NLP, NER Techniques, RAG pipelines, Multi-Agent RAG pipelines, Hybrid search and context similarity techniques.
Strong foundation in statistical theory and its practical applications.
Experience with cloud platforms (Snowpark, Azure ML) and MLOps tools is a plus.
Excellent communication and storytelling skills with data.

Preferred Skills:

Experience in causal inference, A/B testing, and experimental design.
Familiarity with deep learning architectures and NLP techniques.
Exposure to big data tools like Spark, Snowflake, or Databricks.
Domain expertise in [e. g. healthcare] is a plus.

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