Data Scientist
$129,900 - $152,800 per year
Apply (opens in a new tab)Data Scientist
Posted yesterday
SENIORITY
Senior
SALARY
$129,900 - $152,800 per year
About the role
- 2+ years of professional experience as a data scientist including experience developing and releasing predictive models to production
- Bachelor's degree in a technical field such as mathematics, statistics, computer science or economics; Master's degree or PhD in a relevant field preferred.
- Demonstrated success turning businesses problems into data problems and developing innovative and unexpected solutions
- Ability to explain results to technical and non-technical teammates leveraging your communication skills and data visualization
- Demonstrated performance in building machine learning models using standard tools, such as scikit-learn or R, to drive business improvements
- Advanced knowledge of applied mathematics and statistics and their common applications in online businesses
- Experience with or strong interest in understanding and optimizing online auctions for both bidders and sellers
- Experience with or strong interest in optimization using reinforcement learning and contextual multi-armed bandits
- Strong skills in statistical and scientific programming in Python, fluent in SQL, proficient with Jupyter notebooks
- Experience with packaging your code for deployment and reusability
- Passionate about sharing knowledge and mentoring teammates, and communicating designs to technical and non-technical stakeholders
- Keen sense about data science technologies, stay on top of industry trends and actively help the team to expand the tech stack
- Entrepreneurial mindset, want to grow a business, and love working with an Agile team
- Thrive in a fast-paced work environment where everyday contributions have a big impact
- Bachelors degree in a technical field, with an advanced degree in Data Science, Computer Science, Math/Statistics, or a related field strongly preferred
- Internship or equivalent professional experience in Data Science/MLE required. At least 2 years of professional experience in Data Science/ML preferred (preferred more strongly for candidates without an advanced degree)
- Proven experience building and delivering ML solutions in a production eng environment preferred
- Languages: Python, SQL (other languages a plus but not required)ML Operations and comfortability with the model development lifecycle and related technologies (Snowflake/analytics DBs, AWS SageMaker or similar ML Platforms, MLFlow, GitHub, etcetera)
- Comfortable working in a production engineering environment
- Experience with predictive modeling (classification/regression) and experimentation (reinforcement learning and work with generative ML/AI is a plus)
- Strong fundamentals in modeling and ML, and related technologies
- Strong fundamentals in software development, with an emphasis on coachability
- Strong stakeholder management abilities, with a knack for understanding user needs and aligning them with technical solutions
- Strong product sense and the ability to contribute to understand product strategy and roadmap discussions
- Outstanding communication and interpersonal skills, with the ability to articulate complex technical concepts clearly
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
