Lead Data Scientist
3 weeks ago
Responsibilities :
Data Analysis and Insights :
- Analyze large datasets to derive meaningful insights with demonstrable results.
- Apply rigorous experimentation and iterative analytics to drive product improvements using data science methodologies.
Algorithm Development :
- Create algorithms to extract information from large datasets and perform statistical analysis.
- Develop predictive models to forecast outcomes and trends.
Dashboard Creation and Visualization :
- Design and develop dashboards and visualizations for monitoring key metrics and performance indicators.
- Distill complex results or processes into simple, clear visualizations.
Customer Requirement Interpretation :
- Translate informal customer requirements into well-defined problem definitions, addressing ambiguity and competing objectives.
Documentation :
- Document end-to-end processes in a presentable format for internal and external stakeholders.
Data Gathering and Pre-processing:
- Collect and preprocess relevant data for insight generation and model building.
Data Interpretation and Reporting :
- Interpret data to generate actionable insights and explain findings in an understandable manner.
- Automate report generation using visualization tools.
Algorithm Deployment :
- Deploy data science and technology-based algorithmic solutions to address business needs effectively.
Analytical Techniques :
- Apply appropriate analytical techniques such as exploratory data analysis, regression analysis, decision trees, clustering, etc., to solve complex problems.
Requirements :
- Strong analytical skills with a proven track record of delivering impactful insights.
- Proficiency in data visualization and presentation.
- Expertise in Python/R, SQL, and Excel for data analysis and manipulation.
- Knowledge of AWS (Amazon Web Services) and Git.
- Understanding of statistical concepts and proficiency in machine learning models.
- Familiarity with data science tools, algorithms, and methodologies.
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