Data Scientist - GJT
Maharashtra, Mumbai, India
Python
R
NumPy
Pandas
Scikit-learn
TensorFlow
PyTorch
SQL
AWS
Azure
GCP
Spark
Hadoop
Airflow
Tableau
Power BI
Matplotlib
Seaborn
We are looking for a Data Scientist to analyze large datasets, develop machine learning models, and generate actionable insights that drive business decisions. The ideal candidate has a strong foundation in statistics, programming, and data engineering, along with experience in deploying AI/ML solutions.
Key Responsibilities:
- Collect, process, and analyze large datasets from multiple sources to extract actionable insights.
- Develop predictive models, machine learning algorithms, and statistical analyses to solve business challenges.
- Collaborate with cross-functional teams (engineering, product, marketing) to integrate data-driven solutions into business processes.
- Optimize data models and pipelines for scalability and performance to ensure efficient data processing.
- Visualize insights and present findings to both technical and non-technical stakeholders in a clear and impactful manner.
- Stay up to date with the latest advancements in AI/ML and data science technologies and apply them to solve business problems.
Required Skills & Qualifications:
- Minimum of 5+ years of experience in data science, machine learning, or analytics roles.
- Proficiency in Python/R and libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, and PyTorch.
- Strong SQL skills for querying databases and working with large datasets.
- Knowledge of cloud platforms (AWS, Azure, GCP) and data engineering tools (Spark, Hadoop, Airflow).
- Experience with data visualization tools such as Tableau, Power BI, Matplotlib, and Seaborn.
- Strong problem-solving, analytical, and communication skills, with the ability to translate complex technical concepts into understandable insights.
Preferred Qualifications:
- Exposure to Deep Learning and Natural Language Processing (NLP) techniques.
- Understanding of MLOps and experience with deploying ML models into production environments.
- Experience working with Big Data technologies and handling large-scale datasets.
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