Wait, What Do You Do?

<div class="content-intro">Immigration / Work Authorization Notice: Applicants must be currently authorized to work in the United States. iSpot is not able to sponsor or take over sponsorship of an employment visa for this position at this time. iSpot competes for the best talent. Our compensation packages consist of salary and equity in one of Seattle’s hottest start-ups, as well as other standard benefits. Most importantly, we provide a really interesting working experience, and the chance to contribute to the success of something great.</div>What You’ll Be Part Of: Our Client Data Science team is dedicated to delivering invaluable insights and reports to our clients. We thrive on innovation, employing cutting-edge techniques that empower our clients to advance their businesses. Comprising Analysts, Data Scientists, and Engineers, our team brings a deep understanding of the media landscape, advanced data science techniques, and strong coding skills, all fueled by a passion for growth. Responsibilities: As a key member of the Client Data Science team, you will be responsible for a variety of critical tasks, including: <div class="s24">● Managing, mentoring and growing three direct reports as well as fostering growth of the entire Data Science team.</div> <div class="s24">● Collaborating on complex problems, both independently and as part of a team, while writing and optimizing R, Python, or SQL scripts for effective data processing.</div> <div class="s24">● Adapting existing tools and methods to meet evolving needs, balancing workloads across various projects, and leveraging solid machine learning and statistical skills to inform data-driven decisions.</div> <div class="s24">● Collecting, aggregating, and manipulating data from multiple sources, applying analytical techniques to derive insights, and creating clear visualizations or reports.</div> <div class="s24">● Engaging with internal and external teams to clarify requirements, address challenges, and develop tailored solutions, while documenting project status and updates in tools like JIRA.</div> <div class="s24">● Communicating effectively with diverse audiences, translating complex findings into accessible formats through written reports and presentations, and actively participating in team discussions to support collaboration and problem-solving.</div> <div class="s24"> </div> <div class="s24">Qualifications and Education Requirements:</div> <div class="s27">● Experience: 5+ years of experience in Analytics, Data Science, or a comparable field</div> <div class="s27">● Education: Bachelor's degree in a quantitative or social science field, Master's/PhD preferred</div> <div class="s27">● Coding Experience: 3+ years coding experience with 2+ years coding specifically in R or Python;</div> <div class="s27">● Coding Skill: Advanced coding skill in Python, or R;</div> <div class="s27">● Management Experience: 1+ years of people management or people mentorship;</div> Preferred Skills: <div class="s27">• Technical Knowledge: Intermediate knowledge of Analytics, Data Science, Statistics, Marketing, and Visualizations;</div> <div class="s27">• Communication: Exceptional written and verbal communication with internal and external stakeholders at all levels;</div> <div class="s27">• iSpot’s Client Data Science team expects all candidates to have a range of soft skills, including but not limited to: critical thinking, attention to detail, and effective communication. Additionally, the following soft skills are required for success in this role: Problem solving; Empathy; Leadership.</div>   Target cash compensation range: $136,000-168,000 USD Annually We are committed to providing competitive, market-informed compensation. The cash compensation above includes base salary, variable commission for employees in eligible roles, and annual bonus targets for eligible roles. In addition to cash compensation, all full time iSpotters are eligible to participate in iSpot’s equity plan to receive stock options. Non-exempt roles will also be eligible for (pre-approved) overtime pay. Individual compensation packages are influenced by different factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. For more information on total rewards package, go<a href="https://www.ispot.tv/about/careers"> HERE</a> Hybrid & Flexible Workplace Policy iSpot supports a hybrid and flexible workplace. Depending on location and work responsibilities, employees may be designated as full-time or part-time office-based or a fully remote employee. A hybrid work schedule indicates that you work in the office some days and work from home other days. The best hybrid workplaces allow for flexibility while also encouraging consistency.  Those local or living in surrounding areas to one of our offices (Bellevue, WA or New York, NY) will work a hybrid schedule, coming into their local office 1-3 days a week. While those in a role, not office-based and located further away from our offices, will work a fully remote schedule. If you have questions regarding exact details of our hybrid & flexible workplace policy, please let your recruiter know and they will discuss with you further. #LI-REMOTE<div class="content-conclusion">If you don't feel you met every single requirement for the role, don't rule yourself out. Please apply anyway! iSpot is an equal opportunity employer. All applicants will receive consideration for employment without regard to race, ethnicity, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please contact our HR team. California Residents applying for positions at <a class="c-link" href="http://ispot.tv/" target="_blank" data-stringify-link="http://iSpot.tv" data-sk="tooltip_parent" data-remove-tab-index="true">iSpot</a> can access our California Consumer Privacy Act <a href="https://www.ispot.tv/privacy" target="_blank">here.</a></div>

Manager, Client Data Science