Data Scientist

Inclusively is partnering with one of the largest transportation networks to hire a Data Scientist, Decisions, Rider Experience. Please note: this role is NOT an internal position with Inclusively but with the partner company.ABOUT INCLUSIVELY:Inclusively is a digital tech platform that empowers job seekers with disabilities, caregivers, and veterans by using Success Enablers–accommodations and personalized workplace modifications that help all job seekers reach their full potential and excel. This includes all disabilities under the ADA, including mental health conditions (e.g. anxiety, depression, PTSD), chronic illnesses (e.g. diabetes, Long COVID), and neurodivergence (e.g. autism, ADHD).Create your profile, select Success Enablers, and connect to jobs from our partnered employers who are committed to creating diverse and inclusive teams. However, Inclusively does not require candidates to disclose their specific disability to join the platform.As a Data Scientist, Decisions in the Rider team, you will leverage data and rigorous analytical thinking to shape our rider app and make business decisions that put our customers first. You will identify and scope opportunities, shape priorities, recommend technical solutions, design experiments, and measure impact. You will bring a quantitative mindset to decision-making in partnership with product, design, engineering, business, and operations stakeholders throughout the organization.You will report to a Data Science Manager in the Rider Science team.Responsibilities:Leverage data and analytic frameworks to identify opportunities for growth and efficiencyPartner with product managers, engineers, marketers, designers, and operators to translate data insights into decisions and actionsDefine experimentation best practices, design and analyze online experiments; communicate results and facilitate launch decisionsEstablish metrics that measure the health of our products and rider experienceLead deep dives into rider experience and marketplace data to uncover new product and business opportunitiesFacilitate and foster data-driven and informed decision making and prioritizationPresent findings, recommendations, and results to senior leadership and cross-functional stakeholdersExperience:Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experienceMinimum 5+ years experience in strategic data science roles in a technology company, management consulting, investment firms, or an equivalent analytical role in a high growth startupExperience in leading high visibility projects and influencing others in a cross-functional team environmentProficiency in SQL - able to write structured and efficient queries on large data setsExperience in programming, especially with data science and visualization libraries in PythonExperience in online experimentation and statistical analysisStrong oral and written communication skills, and ability to collaborate with and influence cross-functional partnersBenefits:Great medical, dental, and vision insurance optionsMental health benefitsFamily building benefitsIn addition to 12 observed holidays, salaried team members have unlimited paid time off, hourly team members have 15 days paid time off401(k) plan to help save for your future18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligiblePre-tax commuter benefitsThis role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Thursdays and a team-specific third day. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #HybridThe expected base pay range for this position in the San Francisco area is $144,000 - $180,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

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