Data Scientist
7 days ago
Job Description for Data Scientist
We are seeking a skilled Data Scientist with over 3 years of experience in data science, particularly in the Retail, FMCG, or CPG domains. The ideal candidate will possess comprehensive expertise in building and deploying data models from start to finish, showcasing a strong background in statistical analysis, machine learning, and predictive modeling.
Key Responsibilities :
- Develop and implement end-to-end data models, with a minimum of 2-3 completed projects that involve model creation, training, validation, and deployment.
- Conduct advanced statistical analysis and apply techniques such as time series analysis, forecasting, clustering, segmentation, optimization, and linear regression to solve complex business challenges.
- Utilize Python and PySpark for data processing, analysis, and model development to provide scalable and efficient solutions.
- Engage in predictive modeling to identify trends and patterns that drive business insights and decision-making.
- Work collaboratively with cross-functional teams to understand project requirements, refine data sources, and deliver actionable insights.
- Communicate findings clearly and effectively to both technical and non-technical stakeholders, translating complex data results into strategic recommendations.
- Stay current with industry trends and advancements in data science methodologies and tools to continuously improve model performance and analytical capabilities.
Preferred Experience :
- Experience in the Retail, FMCG, or CPG sectors is highly desirable, as it ensures a better understanding of market dynamics and consumer behavior.
- Strong coding skills in Python and PySpark, with the ability to write clean, efficient, and well-documented code.
- Expertise in time series forecasting, segmentation analysis, clustering algorithms, and optimization models.
Qualifications :
- Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or a related field.
- A proven track record of end-to-end model development, from data collection and preprocessing to model evaluation and deployment.
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