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Eight Sleep is a pioneering company focused on sleep fitness, aiming to enhance human potential through improved sleep. Their innovative approach leverages technology and science to provide personalized solutions that radically change nighttime routines for better health and happiness. Their flagship product, the Pod, has been recognized by Fast Company as one of the Most Innovative Companies and featured in TIME’s Best Inventions of the Year.
The company is expanding its team and looking for an experienced Data Scientist specifically skilled in working with sales and marketing data. The desired candidate should have a proven track record in building complex predictive demand models, which will support the company's growth strategies. The main responsibilities include:
Developing and maintaining predictive models for sales growth, customer behavior, and lifetime value.
Creating a Media Mix Model to assess different spending scenarios across various marketing channels.
Collaborating with the Growth and Finance teams, providing insights into potential opportunities for incremental revenue growth.
Leading quantitative analyses to furnish insights for key stakeholders like the CEO, CFO, and VP of Growth regarding marketing performance and member behavior.
Establishing and maintaining dashboards for key marketing metrics, enhancing transparency and monitoring.
Conducting full-cycle analytics experiments and reporting with tools such as SQL, R, and Python.
Identifying growth opportunities in the marketing funnel and translating insights into actionable recommendations.
Building analytical ETLs that support data science models.
Candidates for this role are expected to hold a Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, or a related field. The following qualifications are essential:
A minimum of 3 years of experience in data science, ideally in a marketing or growth-focused role.
Proficiency in SQL and data visualization tools like Looker or Tableau.
Experience with programming languages such as Python or R.
Familiarity with constructing data pipelines (ETL) using tools like dbt.
Strong analytical and problem-solving skills that allow for effective decision-making.
Ability to synthesize complex information and manage data to drive business decisions.
Eight Sleep fosters a collaborative and passionate workplace where employees are expected to significantly impact the sleep fitness category. The company emphasizes wellness and career development, offering several attractive benefits:
All full-time employees receive the Pod, enhancing their sleep quality.
There is a commitment to flexible Paid Time Off (PTO), allowing employees to recharge and maintain work-life balance.
Opportunities for role ownership and unlimited growth potential are readily available as the company expands.
Eight Sleep celebrates diversity and promotes inclusivity, ensuring that every employee feels valued and has the chance to thrive.
Compensation details for this role are competitive and contingent upon location. While specific salary figures are not disclosed, the company mentions the inclusion of equity as part of the compensation package.
This position is open to applicants located in the US, Canada, LATAM, UK, or various locations across Europe. This international scope offers flexibility for candidates located within these regions to apply, making it a suitable opportunity for remote work seekers.
In conclusion, the Data Scientist role at Eight Sleep presents a significant opportunity for professionals aiming to apply their data science skills to impactful marketing strategies. The company’s commitment to innovation, employee well-being, and diversity make it an attractive workplace for potential candidates. If you are experienced in data analytics and looking to contribute to a cutting-edge company dedicated to the evolution of sleep, this is an excellent position to consider.
This job offer was originally published on jobicy.com
This job offer summary has been generated using automated technology. While we strive for accuracy, it may not always fully capture the nuances and details of the original job posting. We recommend reviewing the complete job listing before making any decisions or applications.
