Data Scientist 2 4P187
Data Scientist 2 4P187
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Job Description
Overview:
A Data Scientist with 5 to 10 years of experience is responsible for leveraging data to uncover insights create predictive models and drive datadriven decisionmaking within an organization. This role requires advanced analytics machine learning expertise and strong problemsolving skills to extract actionable intelligence from large and complex datasets.
Key Responsibilities:
1. Data Analysis:
Collect clean and analyze complex datasets to uncover trends patterns and actionable insights.
Apply statistical techniques to derive meaningful information for business strategies.
2. Predictive Modeling:
Develop and deploy machine learning models to forecast future trends behaviors and outcomes.
Utilize techniques such as regression analysis classification and clustering.
3. Data Visualization:
Create compelling visualizations using tools like Tableau Power BI and Python libraries (e.g. Matplotlib Seaborn).
Effectively communicate insights to both technical and nontechnical stakeholders.
4. Hypothesis Testing:
Formulate and test hypotheses to statistically validate business decisions and recommendations.
5. Feature Engineering:
Engineer and select relevant features to optimize the performance of machine learning models.
6. Algorithm Development:
Build and finetune machine learning algorithms such as decision trees random forests and neural networks.
7. Data Integration:
Collaborate with IT and database administrators to access and integrate data from multiple sources and data warehouses.
8. Model Deployment:
Deploy machine learning models into production environments to support realtime analytics and decisionmaking.
9. A/B Testing:
Design and evaluate A/B tests to assess the impact of process or product changes.
10. Data Ethics:
Ensure data handling practices meet ethical standards including privacy and compliance with regulations.
11. Crossfunctional Collaboration:
Work closely with engineers business analysts and domain experts to align data initiatives with business goals.
12. Mentorship:
Provide guidance and mentorship to junior data scientists and analysts to support team development.
13. Continuous Learning:
Stay updated on the latest data science tools trends and best practices through professional development.
Qualifications:
Education: Bachelors degree in a quantitative field (e.g. Computer Science Statistics Mathematics Engineering).
Masters or Ph.D. is a plus.Experience: 5 to 10 years in data science with experience in machine learning and statistical analysis.
Programming Languages & Tools: Proficiency in Python R or Julia.
Visualization Tools: Experience with Tableau Power BI and Python visualization libraries (Matplotlib Seaborn).
Database Skills: Strong understanding of databases and SQLbased data manipulation.
Additional Skills:
Advanced problemsolving and critical thinking abilities.
Strong communication skills for conveying technical findings to diverse audiences.
Familiarity with big data and distributed computing frameworks (e.g. Hadoop Spark) is a plus.
Awareness of data ethics and regulatory compliance.
Employment Type
Contract
