We are looking for a talented, motivated and experienced Data Scientist to join our team at Rezi. As a Data Scientist, you will be responsible for developing algorithms, analyzing data and building data-driven applications. You should have a strong understanding of statistics, big data, machine learning and data visualization.Your responsibilities will include gathering and analyzing large datasets, building predictive models, developing data-driven applications and developing algorithms to automate data-driven processes. You should also be able to create data visualizations to present complex data in an easy-to-understand format. You should be able to work independently and collaboratively with a team of data scientists. You should have strong problem-solving and communication skills. Ultimately, you should be able to help us make informed decisions based on our data.
• As a Data Scientist at Rezi, responsible for developing data-driven insights on product performance, customer behavior, and our overall business
• Analyze large volumes of data to design and build predictive models, identify trends, and create insights that can be used to inform product decisions
• Create and maintain comprehensive data pipelines to ensure accuracy and reliability of the data
• Create visualizations to communicate insights to stakeholders and drive meaningful action
• Collaborate with cross-functional teams such as product, engineering, and design to ensure data-informed product development
• Develop and maintain data governance standards and processes to ensure data accuracy and reliability
• Stay up to date on industry trends and best practices in data science and machine learning
• 7+ years of data science experience.
• Expertise in statistical and machine learning techniques (e.g. regression, clustering, decision trees, deep learning, NLP, etc).
• Experience in developing predictive models and advanced analytics solutions.
• Proficiency in scripting languages such as Python, R, and/or MATLAB.
• Experience working with large datasets and databases such as Hadoop, Apache Spark, etc.
• Ability to communicate complex technical concepts to non-technical stakeholders.
• Good understanding of data engineering and data visualization technologies (e.g. Hive, Tableau).
• Working knowledge of software engineering practices and software development life cycles.
• Proven ability to document processes, findings, and recommendations.