Posted:1 day ago|
Platform:
On-site
Full Time
- Data Preprocessing: Organize, categorize, and prep data for processing. Identify incomplete, incorrect, inaccurate or irrelevant portions of data and interpret, cleanse or replace/deleted them as needed.
- Advanced Data Analysis: Utilize advanced statistical techniques to analyze complex, large sets of data, and extract actionable insights that will help drive decision-making processes across various functions of the business.
- Model Development: Develop, refine, and implement machine learning algorithms and statistical models that will help create data-driven solutions to business problems. Also responsible for validating and testing these models to ensure accuracy.
- Collaboration: Work closely with the team of engineers and product designers to understand technical and business requirements, convert these to analytic solutions, and integrate them into our product suite.
- Insight-Driven Business Decisions: Utilize and translate complex results from the data analyses and models into strategic recommendations for both technical and non-technical stakeholders.
- Presentations: Represent the data science team in cross-functional teams to ensure correct and impactful data science principles are incorporated. Effectively present complex statistical concepts and results, as well as their implications, to a non-technical audience.
- Mentoring and Leadership: Provide mentorship and guidance to junior data scientists in the team, educate them on best practices, and guide them in their career paths.
- Minimum of five years of working experience as a data scientist.
- Strong knowledge of machine learning models, data mining, and databases.
- Experience with programming languages such as Python, SQL, etc.
- Exceptional problem-solving skills, attention to detail, and a team player.
- Strong communication skills, with the ability to present complex technical findings to non-technical stakeholders.
- Experience in mentoring junior data scientists or leading a data science team is preferred.
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