Senior Data Scientist
Remote
Going
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As the Senior Data Scientist at Going, you will play a pivotal role in shaping the future of travel exploration and recommendations. Leveraging your expertise in data science and machine learning, you will spearhead the development and implementation of advanced algorithms and models that deliver personalized and compelling travel recommendations tailored to individual travel goals. Working closely with cross-functional teams, you will translate business requirements into innovative data science solutions, from feature engineering and model development to optimization and deployment. Your strategic leadership will shape the future of our data science capabilities, driving continuous innovation and enhancing the user experience. If you're passionate about utilizing data to unlock new possibilities in the travel industry and thrive in a dynamic environment that blends both autonomy with support , we invite you to join us on our mission to redefine travel discovery for millions of users worldwide.
Due to the high volume of applicants we expect to receive for this role, we will be closing applications 4/19/24 to ensure we can review and respond to all candidates that have applied.
In the short term, you will
Understand the short and long-term vision of the company. In collaboration with Product and Engineering leadership, define the roadmap for advancing our data science capabilities in travel recommendation and ensure alignment with product development timelines.
Work closely with product managers, designers, and business stakeholders to understand user needs and business requirements and translate them into actionable data science solutions.
Collaborate with data engineers to design and optimize data pipelines for efficient model training and inference.
Utilize large-scale datasets to extract meaningful insights and identify patterns that drive actionable, delightful recommendations for users.
Evaluate the technology needs for the data science domain and actively advocate for scalable solutions where necessary.
In the long term, you will
Implement the data science domain strategy that aligns with the overall vision by organizing and actioning tactical initiatives to deliver the vision.
Lead end-to-end development of machine learning models and algorithms for travel discovery, from data collection and preprocessing to model training, evaluation, and deployment.
Explore novel approaches in collaborative filtering, content-based filtering, and hybrid models to enhance recommendation quality and diversity.
Engineer and refine features from diverse datasets, ensuring models leverage user interactions, historical data, and relevant external factors for accurate predictions.
Optimize models for speed and efficiency, continuously iterating to adapt to evolving user preferences, market trends, and business dynamics.
Implement an experiments and A/B testing framework to enable opportunity discovery by product managers.
Spearhead model evaluation and improvement cycles using robust metrics, experimentation, and A/B testing to enhance accuracy and user satisfaction.
Innovate in recommendation engine development, employing collaborative and content-based filtering to curate highly personalized travel suggestions.
Foster a culture of excellence and continuous learning within the team, mentoring junior members and sharing knowledge to uplift organizational expertise in data science.
What you know
5+ years of hands-on experience in data science, machine learning, and predictive analytics, with a proven track record of delivering innovative solutions, preferably in travel or e-commerce industries.
Proficiency in programming languages such as Python (or R, but we typically use Python here), and experience with data science libraries/frameworks.
Deep knowledge of machine learning algorithms including supervised learning (e.g., classification, regression), unsupervised learning (e.g., clustering, dimensionality reduction), and semi-supervised learning.
Thorough understanding of statistical methods, probability theory, and mathematical concepts underlying machine learning algorithms.
Hands-on experience with deep learning frameworks and familiarity with convolutional neural networks (CNNs), recurrent neural networks (RNNs), and attention mechanisms.
Ability to design and optimize scalable data processing pipelines for handling large volumes of structured and unstructured data efficiently.
Demonstrated understanding of software engineering principles and best practices, including version control (e.g., Git), code review, and collaborative development workflows.
Excellent communication skills and ability to articulate complex concepts and findings to both technical and non-technical stakeholders.
Genuine passion for travel and exploration, with a deep understanding of the travel industry landscape, trends, and consumer behavior.
Enthusiasm for leveraging data science and technology to drive innovation and create impactful solutions that enhance the travel discovery experience for users.
You’re legally authorized to work in the United States and able to work US-hours.
If you find yourself excited about the opportunity but worried you might not meet every requirement, we encourage you to still apply.
We appreciate that skill and talent come in many forms and are often built from a diverse set of experiences. We're on the lookout for people who are passionate about what we do and are eager to bring their unique contributions to our team. If that sounds like you, we'd love to see your application and learn more about you.
Technologies We Use
Python and Airflow are our core technologies for data processing and workflow automation.
We use Snowflake, dbt, and Preset for our data warehousing and analytics.
We use SageMaker, Athena, and Glue for our machine learning and data querying needs.
Starburst for querying data across different databases.
Postgres and Posthog are our database management and product analytics tools.
Who you’ll work with
You will report to Jordan Wyberneit, Director of Data & Insights
You’ll work closely with our Data Engineers, Pedro Pereira & Andrew Fares
You’ll collaborate closely with Chris Pranger, Data Analyst
You’ll also work closely with our Engineering and Product teams
Why you might love working here
The salary for this role starts at $152,646 + equity.
100% remote work environment, so go ahead and bring your dog to work or wear your PJ's to the office!
$700/Quarter Work & Wellness Stipend
Open vacation policy, with a 15 days minimum!
Comprehensive health, vision, dental, and life insurance
401(k) with a 5% match
Up to 12-weeks of paid family leave
No Meeting/Flex Fridays
Meetup stipend when you cross paths with a co-worker
Continuing education & development reimbursement
Bi-annual team retreats (In October, we went to Vancouver. In April we’re headed to Punta Cana!)
Challenging problems to solve and an awesome team to collaborate with every single day
We want you to bring your authentic self to work every single day. We accept you for who you are and consider everyone on an equal opportunity basis without regard to ancestry; age; appearance; color; gender identity and/or expression; genetics; family or parental status; marital, civil union, or domestic partnership status; mental, physical, or sensory disability; national, social or ethnic origin; past or present military service; sexual orientation; socioeconomic status; race; religion or belief. Going is an E-Verify employer.
If you require a reasonable accommodation or assistance for any part of the interview and employment process, please contact us at careers@going.com and let us know the nature of your request.
Tags: A/B testing Airflow Athena Classification Clustering Data pipelines Data Warehousing dbt Deep Learning E-commerce Engineering Feature engineering Git Machine Learning ML models Model training Pipelines PostgreSQL Probability theory Python R SageMaker Snowflake Statistics Testing Unstructured data Unsupervised Learning
Perks/benefits: 401(k) matching Career development Equity Flex vacation Health care Home office stipend Insurance Parental leave Team events Wellness
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