Solve complex problems and drive business decisions using data.
Requirements
- Proficiency in scripting languages like Python and R.
- Experience with SQL and familiarity with databases like Snowflake and Oracle.
- Experience with data visualization tools like Tableau or PowerBI.
- Solid understanding of mathematics, statistics, algorithms, and hands-on experience with machine learning/statistical techniques, including regression, classification, and ensemble methods.
- Familiarity with cloud services like AWS, Google Cloud, and Azure.
- Proficiency in relational data modeling.
- Familiarity with version control systems like Git.
Responsibilities
- Analyze large, complex datasets to extract insights and determine appropriate techniques to use
- Build predictive models, machine learning algorithms and conduct A/B tests to assess the effectiveness of models.
- Present information using data visualization techniques.
- Develop and implement real-time machine learning models for various projects.
- Write well-structured, detailed, and compute-efficient code in Python to facilitate data analysis and model development.
- Utilize IDEs such as Jupyter Notebook, Spyder, and PyCharm for coding and model development.
- Apply agile methodology in project execution, participating in sprints, stand-ups, and retrospectives to enhance team collaboration and efficiency.
Other
- Collaborate with different teams (e.g., product development, marketing) and stakeholders to understand business needs and devise possible solutions.
- Stay updated with the latest technology trends in data science.
- Engage with clients and consultants to gather and understand project requirements and expectations.
- Excellent problem-solving skills and the ability to manage multiple tasks.
- Strong communication skills to effectively collaborate with teams and explain complex results to non-technical stakeholders.
