Leveraging experience to deliver impactful data-driven solutions for complex business challenges.
Requirements
- Demonstrated proficiency in Python, SQL, and data visualization tools (such as Tableau, Power BI, or similar).
- Strong experience in cleaning, transforming, and visualizing large data sets.
- Proven ability to develop, test, and deploy predictive models and machine learning algorithms.
- Advanced understanding of a wide array of machine learning and statistical techniques, with a track record of choosing the right model for the right problem.
- Familiarity with big data technologies (such as Hadoop, Spark, or similar) and cloud computing services (AWS, Azure, GCP) is desirable.
- Strong analytical and quantitative problem-solving ability.
- Experience in effectively communicating complex analytical findings and conclusions to non-technical stakeholders, including the creation of clear and actionable reports.
Responsibilities
- Design and implement advanced statistical models and machine learning algorithms to solve specific business problems.
- Interpret and analyze data from multiple sources to provide actionable insights and recommendations.
- Collaborate with business strategists to understand their needs and provide data-driven guidance.
- Take initiative in identifying opportunities for data analytics to add value to the business.
- Ensure data quality and integrity throughout all processes.
- Effectively communicate findings to stakeholders through visualization and presentations, translating complex data into clear business terms.
- Mentor Associate Data Scientists and contribute to their professional development.
Other
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Operations Research, Engineering, Physics, or another quantitative discipline with 5-6 yrs experience, or Master’s degree with 4 years of experience.
- Demonstrated ability to work independently on complex projects with minimal supervision as well as collaboratively with a team.
- A history of driving projects to completion and contributing to the success of those projects.
- Ability to mentor and support Associate Data Scientists in their technical development.
- Commitment to continuous learning and staying current with industry trends and best practices in data science.
