Data Scientist II at LexisNexis applying statistical analysis and building predictive models for fraud and credit risk. Collaborating with teams to enhance existing products and provide actionable insights.
About the role
- Data Scientist at ZELP analyzing large datasets and developing data-driven solutions for agriculture. Collaborating with stakeholders and implementing machine learning models to address business challenges.
Responsibilities
- Collaborate with stakeholders to identify and understand business needs, translating them into data-driven solutions.
- Design, implement, and maintain robust data pipelines for collecting, cleaning, transforming, and analysing large datasets.
- Perform exploratory data analysis (EDA) to uncover trends and patterns.
- Develop and apply advanced statistical and machine learning models to solve business problems, including forecasting, segmentation, optimization, and predictive modeling.
- Conduct rigorous data analysis, interpret results, and communicate findings to technical and non-technical audiences in a clear and compelling manner.
- Develop and maintain interactive dashboards and visualizations to effectively present data insights and support decision-making.
- Stay abreast of emerging technologies and industry best practices in data science, continuously exploring opportunities for innovation and improvement.
- Contribute to the development of a data-driven culture within the organization, promoting the value of data-informed decision-making.
Requirements
- 4+ years of experience in data science, analytics, or a related field.
- Proven experience working with large datasets and statistical modeling.
- Proficiency in programming languages such as Python or R, with a strong understanding of object-oriented programming concepts.
- Experience in designing and implementing ETL pipelines, data warehousing, and data modeling.
- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Expertise in statistical modeling, machine learning algorithms, and data mining techniques.
- Familiarity with data visualization and reporting tools, such as Tableau, Power BI, or Looker.
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) is a plus.
- Strong analytical and problem-solving skills, with the ability to translate complex data into actionable insights.
- Excellent communication and presentation skills, with the ability to effectively communicate with both technical and non-technical audiences.
- Collaborative mindset and ability to work effectively within cross-functional teams.
Job title
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