Interested in this Data Scientist role at NEX Inc.?
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About This Role
Nex is on a mission to help families rediscover the joy of movement. Created by parents for parents, Nex combines technology and play to deliver fun, social, and interactive experiences powered by natural body motion, encouraging kids and adults to move more, play more, and have fun together. Nex Playground, the company's award\-winning active play system, is purpose\-built to get families moving year\-round, with safety and privacy as core considerations in its intentional design. It is certified kidSAFE\+ COPPA compliant and built to support healthy, active play for all ages and abilities.
Nex Playground features a growing library of 50\+ experiences, including motion and dance games, fitness and educational experiences, and Nex Originals. Content includes collaborations with partners like Hasbro, Sesame Workshop, and NBCUniversal. Nex has been recognized by Fast Company's Most Innovative Companies, TIME's Best Inventions, and Parents' Best Entertainment System for Families, and has earned Red Dot, IDEA, and Core77 international design awards. We encourage you to explore Have Fun and Is Motion Gaming Back?, as they offer a deeper look into our culture, values, and explain how our approach to motion gaming differs from previous generations.
To protect yourself from recruitment scams, please note that Nex communicates through official company emails ending in @nex.inc. If you receive a suspicious email or message, please do not respond and report it immediately to us.
Location: Seattle, WA or Remote US
Annual salary: USD 140,000 \- USD 165,000
Type: Full\-Time
Reports to: Director, Analytics
About this Role
Nex's user base is growing quickly, and the amount of data we're working with is growing even faster. We are seeking an experienced Data Scientist to upgrade our analytics department, and help us understand our customer's needs better than ever before as we launch in several new countries around the world.
The ideal candidate for this role is fundamentally curious about the world, and wants to learn as much as possible about how our customers behave. We want Nex to exist at the forefront of subscription\-based gaming, and give our customers the best gaming experiences for their age ranges, and the person in this role will have the opportunity to design \& carry out the studies that get us there. If you want to work on a small team, for a growing company, and spend your time learning how best to provide value for our customers, we want to hear from you!
### What You'll Do
- Dive deep into customer data: With over a million devices sold, hundreds of thousands of active subscribers and many more on the way, we've barely scratched the surface on how to understand our customers. We have terabytes of data, 10s of billions of rows and counting, for you to play around in.
- Transform questions into actions: We're curious about our customers at all levels of the company, and any given question from any given team can potentially be a worthy avenue of study. Take initiative and spend your time working on taking those questions and running with them.
- Design studies \& automate their upkeep: We don't just want to learn things once—work with other members of the analytics team to make sure that the existing frameworks you come up with keep running as we move onto new ones.
- Write documentation and white papers: Communicate what matters in a manner that is clear, shareable, and can be understood at all levels of the company. Tell us what you've discovered, how you got there, and how we can use it.
### Qualifications
- 4\+ years of experience as a Data Scientist or 6\+ years of experience as a Business Analyst.
- Proficiency in SQL to retrieve data from a Redshift database.
- Proven ability to work independently, without constant guidance.
- Comfortable working in ambiguous environments that require iteration \& investigation.
- Strong written communication skills.
- Bachelor's degree in a quantitative field.
### Preferred Qualifications
- Proficiency in Python or R, in addition to SQL.
- Experience with machine learning tools and/or large data processing frameworks (i.e. Apache Spark).
- Experience with A/B methodology testing.
- Ability to work in cross\-functional environments.
- Ability to thrive and create without the use of AI tools as a baseline.
### What Sets You Apart
- Creative solutions to complex problems.
- Proactive approach to projects.
- Ability to thrive in a fast\-paced environment.
- Experience working with teams from different cultures and backgrounds.
- You're an expert on your own work \& can back up your results.
- Good\-natured and easy to work with.
### We Offer
- Competitive compensation package.
- Flexible working hours and vacation policy.
- Product\-driven culture that treasures talents and individual growth.
- Front\-row seat and hands\-on experience with cutting edge technologies in the evolving gaming field
Nex is located in San Jose, California, USA and Hong Kong. Learn more about us at nex.inc/who\-we\-are.
We encourage applications even if you don't meet more than 50% of the requirements — we believe that experience comes in many forms!
Nex is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, gender identity, and sexual orientation), national origin, ancestry, age, physical or mental disability, medical condition, genetic information, marital status, military or veteran status, or any other characteristic protected by applicable law. This policy applies to all individuals at every stage of the employment relationship, including all current and prospective employees, and covers all employment decisions including recruitment, hiring, job assignment, promotion, compensation, benefits, training, discipline and termination.
We are committed to providing a workplace free from discrimination and harassment and to fostering an inclusive environment for all employees.
Salary Context
This $140K-$165K range is below the median for Data Scientist roles in our dataset (median: $160K across 258 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 4,317 AI roles we're tracking, Data Scientist positions make up 8% of the market. At NEX Inc., this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $192,890 based on 789 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($152K) sits 21% below the category median. Disclosed range: $140K to $165K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
NEX Inc. AI Hiring
NEX Inc. has 1 open AI role right now. They're hiring across Data Scientist. Based in Remote, US. Compensation range: $165K - $165K.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% of all AI roles offer remote work.
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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