Sleeper is hiring for an fresher entry level Data Scientist role in US

Position:

• Data Scientist

Company:

• Sleeper

Location:

• San Francisco, Remote, United States

Job type:

• Full-time

Job mode:

• Remote

Job requisition id:

• Not specified

Years of experience:

• 0–3 years

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Company Description

• Sleeper is a dynamic and innovative tech company that has emerged as a significant player in the digital gaming and fantasy sports ecosystem.

• Based in Las Vegas, NV, the company’s primary focus lies in enhancing the digital gaming experience with a special emphasis on community engagement, interactivity, and mobile-first experiences.

• Sleeper has grown into a household name among fantasy sports enthusiasts due to its commitment to innovation, usability, and exceptional user experiences.

• The company is backed by top-tier Silicon Valley venture capital firms including Andreessen Horowitz, General Catalyst, and Expa, demonstrating its strong financial foundation and belief in its long-term potential.

• At Sleeper, diversity, inclusivity, and fairness are deeply woven into the company’s core values. The company is proud to be an Equal Opportunity Employer and promotes an environment that’s inclusive for all, irrespective of race, gender, age, or ability.

• Sleeper offers competitive compensation packages and benefits, including medical and dental plans, generous paid time off, and a 401(k) retirement plan.

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Profile Overview

• The Data Scientist role at Sleeper is instrumental in advancing product innovation and business growth through deep data insights.

• As part of the Engineering team, the individual will work remotely and collaborate closely with cross-functional departments such as Product, Engineering, and Business Operations.

• The position involves designing scalable data pipelines and shaping the metrics that define success across Sleeper’s product features and strategic initiatives.

• The role focuses on translating complex datasets into meaningful stories, reports, dashboards, and strategies that directly impact product development and business decision-making.

• This role is ideal for someone who thrives in a collaborative environment, is passionate about solving data-driven problems, and is eager to shape product strategies and user experiences using quantitative insights.

• The ideal candidate will be a problem solver who can independently explore datasets and provide actionable intelligence that elevates both product performance and user satisfaction.

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Qualifications

• Strong proficiency in SQL and Python, or equivalent data-centric programming languages, is essential.

• Deep experience working with large-scale data infrastructure and designing high-performance data pipelines.

• Solid foundation in statistics, experimental design (especially A/B testing), and causal inference methodologies.

• Ability to effectively communicate insights to various stakeholders using clear data visualizations and reports.

• Prior hands-on experience in roles such as product analytics, business intelligence, or core data science functions.

• Excellent collaboration skills with the ability to work in a team-oriented environment across multiple departments.

• Adaptability to fast-changing environments and the ability to think both analytically and strategically.

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Additional Info

• Candidates with experience in pricing analytics, user behavior modeling, or demand forecasting in high-frequency transaction systems are encouraged to apply.

• Exposure to real money gaming environments or platforms focused on monetization and user economy will be considered a strong plus.

• Familiarity with Risk & Trading systems, particularly pricing sensitivity models and demand estimation, will set candidates apart.

• The compensation range for this role is broad, reflecting various factors such as experience level, skill set, and geographic location. It ranges from $75,000 to $175,000 annually, in addition to standard benefits like medical, dental, PTO, and retirement plans.

• Sleeper is committed to creating a supportive and accessible workplace for individuals with disabilities and encourages them to request reasonable accommodations if needed.

• All employees and candidates are treated with respect and fairness under the company’s equal employment opportunity policy.

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Responsibilities & Expectations

Data Infrastructure & Engineering Tasks

• Develop, maintain, and scale robust data pipelines to deliver real-time and historical datasets across the organization.

• Ensure reliability and accuracy of core product and business data used for analysis and strategic planning.

• Optimize data architecture and ETL processes to accommodate growing datasets and performance demands.

Metric Development & Performance Monitoring

• Establish and refine KPIs that align with product adoption, user engagement, and overall business success.

• Monitor and track the impact of new product features and changes using data-driven approaches.

• Implement automated systems for real-time metric tracking and alerts.

Experimentation & Impact Analysis

• Design controlled A/B experiments to assess the impact of feature updates, pricing strategies, and UX improvements.

• Conduct deep post-experiment analyses to evaluate user response, retention rates, and revenue shifts.

• Apply statistical rigor to all testing frameworks to ensure valid and trustworthy outcomes.

Data Storytelling & Visualization

• Transform raw data into meaningful stories using compelling dashboards, graphs, and visual tools.

• Deliver actionable insights through reports that are accessible to both technical and business stakeholders.

• Regularly present findings to senior leadership and other departments to inform decision-making.

Cross-Functional Collaboration

• Partner with product managers to define success metrics and refine product strategies.

• Work closely with engineers to ensure data is captured and stored in a usable format.

• Join forces with designers and UX researchers to uncover user trends and behavioral shifts.

• Collaborate with executive leadership to translate business goals into measurable outcomes.

Trend Identification & Opportunity Sourcing

• Explore user behavior datasets to identify latent trends and emerging needs.

• Spot anomalies in data and investigate their root causes.

• Generate hypotheses for new features and improvements based on statistical and behavioral analyses.

Compliance, Accessibility & Ethical Practices

• Adhere to data privacy and security regulations in the handling and processing of user information.

• Ensure analytical models and pipelines align with ethical AI practices.

• Support inclusive data practices and bias mitigation in analytics and insights.

Please click here to apply.

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