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Senior Data Scientist
4 weeks ago
Position : Senior Data Scientist
Experience : 6 years
Required Skills :
- TensorFlow
- PyTorch
- Pandas
- AI/ML
- Python
- MLops
- PySpark
- Azure
Key Responsibilities :
Data Analysis & Modeling : Apply advanced statistical methods, machine learning algorithms, and predictive modeling techniques to solve complex business problems.
Collaborate with Teams : Work closely with cross-functional teams, including business analysts, engineers, and product managers, to understand business needs and provide data-driven solutions.
Data Engineering : Assist in the design and optimization of data pipelines to ensure the availability and accuracy of data for analysis and modeling.
Model Deployment : Lead the deployment of machine learning models and algorithms into production environments, ensuring scalability and maintainability.
Data Visualization & Reporting : Create clear, actionable reports and visualizations to communicate findings to stakeholders across different departments.
Mentorship : Mentor and guide junior data scientists and analysts, providing advice on best practices and complex technical issues.
Research & Innovation : Stay up-to-date with the latest research in data science and machine learning, identifying opportunities for new techniques and technologies that could benefit the organization.
Qualifications :
- Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related field (Ph.D. preferred).
- 5+ years of experience in data science, analytics, or machine learning.
- Strong proficiency in programming languages such as Python, R, or Scala.
- Expertise in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, XGBoost).
- Experience with SQL and working with large-scale databases (e.g., MySQL, PostgreSQL, NoSQL).
- Advanced knowledge of statistical analysis and modeling (e.g., hypothesis testing, regression,
classification, clustering).
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data tools (e.g., Hadoop, Spark) is a plus.
- Strong communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
- Ability to work independently and in teams, with strong problem-solving and analytical skills.
Preferred Skills :
- Experience in industry-specific data science applications (e.g., finance, healthcare, e-commerce).
- Familiarity with data visualization tools (e.g., Tableau, Power BI, D3.js).
- Experience with deploying models in production environments using tools like Docker, Kubernetes, or
cloud-native services.
- Knowledge of deep learning and natural language processing (NLP) techniques is a plus.
