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Data Science Specialist
1 month ago
We seek an experienced Data Science Specialist with a strong background in data analytics, machine learning, and predictive modeling. The ideal candidate should be proficient in deriving business insights from complex datasets, developing and deploying models, and collaborating with cross-functional teams to integrate analytical solutions into production.
The role involves mentorship, research, and documentation to enhance the organization's data science capabilities.
Key Responsibilities- Analyze large and complex datasets to extract meaningful business insights.
- Apply statistical techniques to identify trends, patterns, and correlations in data.
- Perform A/B testing and other experimental methods to optimize business decisions.
- Design, develop, and deploy predictive models using machine learning (ML) and deep learning techniques.
- Optimize and fine-tune ML models for performance, scalability, and accuracy.
- Implement feature engineering techniques to improve model effectiveness.
- Evaluate model explainability and interpretability for stakeholders.
- Collaborate with engineering, product, and business teams to integrate ML models into production.
- Partner with data engineers to ensure efficient data pipelines and ETL processes.
- Work with business stakeholders to translate analytical insights into actionable strategies.
- Develop interactive dashboards and reports using tools like Power BI, Tableau, or Python libraries (Matplotlib, Seaborn, Plotly).
- Present complex data-driven findings in a clear and effective manner to non-technical stakeholders.
- Stay updated on industry trends, emerging technologies, and best practices in data science.
- Explore new ML algorithms and tools to enhance the organization's analytical capabilities.
- Participate in hackathons, workshops, and conferences to foster innovation.
- Provide guidance and mentorship to junior data scientists and analysts.
- Conduct internal training sessions and knowledge-sharing initiatives.
- Maintain comprehensive documentation of algorithms, methodologies, and data pipelines.
- Evaluate compliance with data governance, security, and privacy policies.
- Strong proficiency in Python, R, or SQL for data manipulation and analysis.
- Experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, XGBoost).
- Hands-on experience with Big Data technologies (Spark, Hadoop) is a plus.
- Proficiency in data visualization tools (Power BI, Tableau, Matplotlib, Seaborn).
- Familiarity with cloud platforms (AWS, Azure, GCP) and deployment tools (Docker, Kubernetes).
- Strong knowledge of data structures, algorithms, and statistical modeling.
- Excellent problem-solving and analytical thinking skills.
- Strong communication and presentation abilities.
- Ability to work in cross-functional teams and drive collaborative initiatives.
- Proactive approach towards continuous learning and improvement.
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
- Certifications in Machine Learning, AI, or Cloud Technologies AWS Certified ML, TensorFlow Developer, etc. are a plus.
- Experience in domain-specific analytics finance, healthcare, e-commerce, etc. is desirable.