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Senior Research Data Scientist

iSpot.tvRemote

iSpot.tv 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.

What You’ll Be Part Of:


AniSpotSeniorResearchData Scientist is a key contributor to the future growth of the company, pushing boundaries on what is measurable in the TV viewing and advertising space. The ResearchData Science team builds prototypes for innovations iniSpot’saudience measures, lift analytics, and creative testing. After developing new methodologies and building prototypes, we work with our product and engineering teams to scale our models and solutions to satisfy the needs of brands, publishers, networks, and agencies in a constantly evolving marketing landscape.

Responsibilities:


  • Data Analysis and Modeling: Conduct in-depth data analysis and build advanced statistical models to extract insights from large viewing and demographic datasets.
  • Machine Learning Model Development: Develop, train, and deploy state-of-the-art machine learning models to solve a variety of measurement problems.
  • Data Pipeline Development: Work with our Data Engineering team to design and implement efficient data pipelines to collect, process, and transform data from various sources.
  • Technical Leadership: Provide technical guidance and mentorship to junior data scientists, ensuring best practices and standards are followed.
  • Research and Innovation: Stayup-to-datewith the latest data science techniques, tools, and technologies, and explore novel approaches to solve complex challenges.

Qualifications and Education Requirements:


  • Degree in mathematics, economics, statistics, software engineering, computer science, physics, or other quantitative discipline.An advanced degree is preferred but not required.
  • 5+ years of experience in data science and/or modeling

Preferred Skills:


  • Deep technical understanding of machine learning, statistics, data science, and related fields
  • Expert in several quantitative software tools, particularly Python, R, and SQL; willingness to learn new tools as needed
  • Expert at wrangling data and debugging the results of machine learning systems
  • Experience working with high dimensional data sets
  • Pragmatic, team-oriented; builds rapport and respect
  • Strong communication, writing, and critical thinking skills; attention to detail
  • Track record or desire to mentor top technical talent in the areas of data science, analytics predictive modeling, and machine learning
  • Strong experience in Spark is preferred but not required

Target cash compensation range: €80,000 - 100,000 USD AnnuallyWe 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, goHERE

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; El Segundo, CA; 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-HybridIf you don't feel you met every single requirement for the role, don't rule yourself out. Please apply anyway!iSpot.tv 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 iSpot.tv can access our California Consumer Privacy Act here.

Life at iSpot.tv

iSpot.tv is the leader in real-time TV ad data and analytics. The attention and conversion analytics company measures TV ad activity at scale and directly from 7.3+ million smart TV screens. The proprietary platform measures TV ad impressions in a digital-like manner across linear (national & local), OTT, VOD and DVR environments and across all operators and zip codes. iSpot's attention analytics measure viewer retention and tune-out while ads are playing on the screen. Every ad's attention is measured and benchmarked against industry standards and over time to quickly detect creative wear. iSpot's conversion analytics set the industry standard for TV attribution. By directly connecting TV ad impressions with web, app and other 1st party data, the company's conversion analytics enable rapid, actionable insights on how creative and media on TV drives sales. The company's dashboards, APIs and analytics are utilized by leading brands in every major industry, as well as by TV networks and agencies. More at https://www.ispot.tv.
Thrive Here & What We Value1. Competitive compensation packages (including salary and equity)2. Hybrid and flexible workplace policy3. Equity plan for full-time employees4. Commitment to equal opportunity employment5. California Consumer Privacy Act compliance
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