Apply

Staff Data Scientist

Posted 2024-10-21

View full description

πŸ’Ž Seniority level: Staff

πŸ” Industry: Social network, Crypto

🏒 Company: ZORA

Requirements:
  • Proven ability to lead complex technical projects from concept to completion, especially in greenfield environments.
  • Advanced proficiency in SQL and Python.
  • Experience with DAG creation using tools like Dagster or Airflow.
  • Strong understanding of business metric definition, maintenance, and effective data presentation.
  • Expertise in statistical methods, experimentation design, and A/B testing methodologies.
  • Familiarity with cross-domain and cross-platform tracking and attribution.
  • Experience working with OLAP databases such as BigQuery, Snowflake, or Redshift.
Responsibilities:
  • Manage complex, ambiguous challenges by framing problems, generating hypotheses, and delivering actionable recommendations.
  • Design and build foundational data systems, including ETLs, dashboards, and analytics to support data-driven decision-making.
  • Enable a culture of experimentation by establishing best practices and systems for A/B testing.
  • Develop, monitor, and refine key metrics for products and business performance.
  • Contribute to the development of feed algorithms, recommendation systems, and search functionalities.
  • Collaborate with stakeholders to drive product prioritization and planning based on data-driven insights.
Apply

Related Jobs

Apply

πŸ’Έ 190000 - 260000 USD per year

πŸ” Home services

  • Master’s or Ph.D. in a quantitative field (e.g., Computer Science, Statistics, Mathematics).
  • 7+ years of experience in data science & machine learning, focusing on real-time models and fraud.
  • Expertise in machine learning and deep learning, particularly with large language models.
  • Knowledge of algorithms like Graph NN, Reinforcement Learning, and unsupervised learning approaches.
  • Proven track record in deploying impactful machine learning models.
  • Proficient in SQL and Python, experience with cloud ML solutions.
  • Excellent communication skills for conveying technical concepts.

  • Lead development of machine learning models to improve fraud detection.
  • Implement optimized models for scalable deployment.
  • Collaborate with engineers, data scientists, and product managers on machine learning systems.
  • Foster innovation within the team to solve complex problems.
  • Mentor junior team members and encourage knowledge sharing.
Posted 2024-11-17
Apply
Apply

🧭 Full-Time

πŸ’Έ 190000 - 260000 USD per year

πŸ” Online marketplace for home services

  • Master's or Ph.D. in a quantitative field (e.g., Computer Science, Statistics, Mathematics).
  • 7+ years of experience in data science & machine learning, focusing on real-time models within tech or marketplaces.
  • Expertise in machine learning and deep learning; knowledge of large language models.
  • Proficiency in state-of-the-art algorithms for fraud detection.
  • Proficiency in SQL and Python; experience with cloud ML solutions.
  • Excellent communication skills to convey complex concepts to non-technical stakeholders.

  • Lead development of machine learning models and algorithms for fraud detection.
  • Implement optimized models for seamless deployment and scalability.
  • Collaborate with engineers, data scientists, product managers, and designers.
  • Foster innovation in solving complex business problems.
  • Guide junior team members and promote a culture of learning.
Posted 2024-11-17
Apply
Apply

🧭 Full-Time

πŸ’Έ 190000 - 260000 USD per year

πŸ” Home services / Online marketplace

  • Master's or Ph.D. in a quantitative field (e.g., Computer Science, Statistics, Mathematics).
  • 7+ years of experience in data science & machine learning, specifically focused on real-time ML models and fraud.
  • Expertise in machine learning, deep learning, and large language models.
  • Experience with algorithms such as Graph NN, Reinforcement Learning, and unsupervised learning for fraud detection.
  • Proven track record of deploying impactful machine learning models into production.
  • Proficiency in SQL and Python, with experience in cloud ML solutions.
  • Excellent communication skills to convey complex technical concepts to non-technical stakeholders.

  • Lead development of machine learning models to improve fraud detection across the marketplace.
  • Implement highly optimized models for seamless deployment and scalability in production.
  • Collaborate with engineers, data scientists, product managers, and designers on end-to-end development.
  • Encourage innovation within the team and explore new techniques to solve business problems.
  • Mentor junior team members and promote continuous learning and technical excellence.
Posted 2024-11-17
Apply
Apply

🧭 Full-Time

πŸ’Έ 190000 - 260000 USD per year

πŸ” Home services marketplace

  • Master’s or Ph.D. in a quantitative field such as Computer Science, Statistics, or Mathematics.
  • 7+ years of experience in data science and machine learning, focusing on fraud detection.
  • Expertise in machine learning and deep learning models, including working knowledge of large language models.
  • Familiarity with advanced algorithms like Graph NN, Reinforcement Learning, and unsupervised learning for fraud detection.
  • Proven track record of deploying impactful machine learning models.
  • Proficiency in SQL and Python, with experience in cloud ML solutions.
  • Excellent communication skills for conveying technical concepts to non-technical stakeholders.

  • Lead development of state-of-the-art machine learning models and algorithms to improve fraud detection.
  • Implement highly optimized models for seamless deployment and scalability in production.
  • Collaborate with engineers, data scientists, and product managers on machine learning systems.
  • Foster innovation by exploring new approaches to solve complex business problems.
  • Mentor junior team members and promote a culture of continuous learning.
Posted 2024-11-17
Apply
Apply

πŸ“ United Arab Emirates

🧭 Full-Time

πŸ” Food

🏒 Company: Careem

  • 10+ years of experience in data mining, predictive modeling, time series analysis, machine learning.
  • Expertise in Big Data methodologies and data transformation for structured and unstructured data.
  • Advanced degree in Physics, Statistics, Mathematics, Engineering, or Computer Science.
  • Experience with Deep Learning Techniques like attention and retrieval models.
  • 3-4 years industrial experience in personalization, recommendation, or search.
  • Strong problem-solving skills and proficiency in Python, SQL, Spark, and Hive.
  • Experience with database technologies like Hadoop, BigQuery, Oracle, and MS SQL Server.
  • Familiarity with business intelligence tools such as Tableau and geospatial data processing.

  • Lead a 0-1 AI transformation for Careem app from personalization perspective.
  • Build a long-term vision for customer acquisition and engagement strategies utilizing data.
  • Drive exploratory analysis of user behavior and build models for product enhancements.
  • Shape data/ML models to optimize product experience and identify opportunities.
  • Provide product leadership through data-based recommendations and experimentation results.
  • Implement scalable ML algorithms for production on big data.
  • Conduct exploratory data analysis projects for growth and optimization.
  • Answer complex analytic questions from big data sets.

LeadershipPythonSQLBusiness IntelligenceData AnalysisData MiningHadoopMachine LearningMySQLOracleSAPTableauAlgorithmsData analysisData miningData scienceSparkProblem Solving

Posted 2024-11-07
Apply
Apply

πŸ“ Brazil, US, Sweden

πŸ” Open Banking Payments

NOT STATED

  • Maintain the risk controls at Trustly.
  • Develop machine learning models aimed at mitigating risk.
  • Conduct data analysis to support risk management efforts.
  • Create a framework and infrastructure for managing risk.

PythonData AnalysisMachine LearningNumpyData analysisData science

Posted 2024-11-07
Apply
Apply

πŸ“ UK

🧭 Full-Time

πŸ’Έ 85000 - 90000 GBP per year

πŸ” AI and Data Science

🏒 Company: Prolific

  • Mastery of Data Science Stack: Fluent in Python/R and SQL, with deep expertise in data science libraries (e.g. scikit-learn, pandas). Familiar with MLOps and transitioning models to production.
  • Modeling Expert: Proficient in classical statistical methods and state-of-the-art machine learning techniques.
  • Big Data Proficiency: Comfortable with large-scale data technologies (e.g. Spark) and scaling data processing pipelines.
  • Statistical Rigor: Strong foundation in statistics, capable of designing and analyzing experiments.
  • Data Storytelling: Ability to translate complex analyses into clear narratives through visualization.
  • Project Leadership: Proven track record of leading complex data science initiatives delivering business value.
  • Bar Raiser: Passionate about mentoring junior data scientists and improving team technical standards.
  • Product-Driven Mindset: Ability to balance speed with quality in fast-paced environments.
  • Engineering Best Practices: Knowledgeable in software engineering principles like version control and testing.
  • Influence Without Authority: Effective communication and influence across various organizational levels.
  • Clear Communication: Skillful at simplifying complex technical concepts for diverse audiences.
  • Effective Prioritization: Proficient in managing multiple priorities, focusing on high-impact work.

  • Architecting Data Science Solutions: Lead the conceptualization and planning of data science initiatives that align with and drive key business objectives.
  • Solving Complex Data Challenges: Spearhead the development and implementation of sophisticated data models and algorithms, diving into hands-on coding for the most critical components.
  • Elevating Team Standards: Guide the technical direction of the team through thoughtful code reviews and targeted mentorship, fostering a culture of excellence and continuous improvement.
  • Shaping Product Strategy: Collaborate closely with product managers to identify opportunities where data science can drive product innovation and user value.
  • Influencing Business Decisions: Synthesize complex analyses into actionable insights, presenting compelling data-driven narratives to inform senior leadership's strategic decisions.
  • Advancing Technical Capabilities: Evaluate and implement cutting-edge data science methodologies and tools, ensuring the team stays at the forefront of the field.
  • Optimizing Data Infrastructure: Partner with data engineers to enhance data pipelines, logging systems, and MLOps practices, creating a robust foundation for advanced analytics and modeling.
  • Cultivating Data Science Knowledge: Author technical documentation and thought leadership pieces to disseminate key insights, best practices, and learnings across the organization.

LeadershipPythonSQLMachine LearningStrategyAlgorithmsData sciencePandasSparkMentoring

Posted 2024-10-24
Apply
Apply

πŸ“ United States

🧭 Full-Time

πŸ” E-commerce

🏒 Company: Sparc The World

  • Proficiency in Python.
  • Strong background in mathematics/statistics, probability, and/or machine learning.
  • Familiarity with differentiable programming or probabilistic programming tools (e.g., Tensorflow, Pytorch, JAX, Pyro, PyMC).
  • Ability to articulate findings effectively to non-technical audiences in English.
  • Experience (or a keen interest) in thriving within a small, dynamic company environment.
  • 6+ years of relevant experience.

  • Analyze the correlation between clients' marketing inputs and outputs (sales, revenue) while quantifying associated uncertainties.
  • Translate complex models and their implications into understandable insights for non-technical stakeholders.
  • Collaborate with data engineering and product teams to operationalize solutions for our expanding client base.
  • Engage with customers, product managers, engineers, and support teams to conceptualize, develop, and refine high-impact solutions.
  • Provide technical support and expertise to clients in relevant domains.

PythonMachine LearningPyTorchTensorflowCollaboration

Posted 2024-10-23
Apply
Apply

πŸ“ USA

πŸ” Marketing technology, e-commerce

🏒 Company: Northbeam

  • Bachelor's degree in Mathematics, Computer Science, or a highly quantitative STEM field.
  • Strong understanding of statistics, linear algebra, probability, and machine learning.
  • Experience with regression, time series analysis, causal inference, statistical testing, Bayesian modeling, optimization, or signal processing.
  • Strong programming skills and ability to implement data science solutions using clean, interpretable, and maintainable code.
  • Expertise in Python.
  • Minimum 4+ years of professional experience as a data scientist, ML engineer, or quant, or 2+ years as a data scientist and 2+ years as a Software Engineer.
  • 2+ years of media or advertising experience.

  • Lead R&D for new and existing data science powered products at Northbeam.
  • Collaborate with engineering and product teams to take working proofs of concept into production.
  • Provide technical expertise and support for non-technical stakeholders.
  • Educate colleagues in other departments about the use of data science in marketing and advertising.

LeadershipPythonSoftware DevelopmentData AnalysisMachine LearningNumpyData analysisData sciencePandasCommunication SkillsAnalytical SkillsCollaboration

Posted 2024-10-21
Apply
Apply

πŸ“ Brazil

🧭 Full-Time

πŸ” Commerce

🏒 Company: VTEX

  • Extensive experience building and optimizing ML pipelines using frameworks like Scikit-learn, PyTorch, or TensorFlow.
  • Fluency in designing experiments with statistical rigor, such as A/B tests.
  • Experience handling big data for analysis, feature engineering, and evaluating experiment results.
  • Understanding of differences between research and production-level code.
  • Knowledge of key requirements for deploying and maintaining ML/AI models in production environments.
  • Strong communication skills and the ability to simplify complex technical concepts.

  • Translate business opportunities into technical solutions using ML/AI modeling, statistical data analysis, and experiment design.
  • Act as a bridge between stakeholders to facilitate understanding and promote data-informed decisions.
  • Lead efforts to leverage AI/ML solutions to enhance VTEX products and seize strategic opportunities.

PythonData AnalysisPyTorchData analysisTensorflowCommunication SkillsCollaboration

Posted 2024-10-17
Apply

Related Articles

Remote Job Certifications and Courses to Boost Your Career

August 22, 2024

Insights into the evolving landscape of remote work in 2024 reveal the importance of certifications and continuous learning. This article breaks down emerging trends, sought-after certifications, and provides practical solutions for enhancing your employability and expertise. What skills will be essential for remote job seekers, and how can you navigate this dynamic market to secure your dream role?

How to Balance Work and Life While Working Remotely

August 19, 2024

Explore the challenges and strategies of maintaining work-life balance while working remotely. Learn about unique aspects of remote work, associated challenges, historical context, and effective strategies to separate work and personal life.

Weekly Digest: Remote Jobs News and Trends (August 11 - August 18, 2024)

August 18, 2024

Google is gearing up to expand its remote job listings, promising more opportunities across various departments and regions. Find out how this move can benefit job seekers and impact the market.

How to Onboard Remote Employees Successfully

August 16, 2024

Learn about the importance of pre-onboarding preparation for remote employees, including checklist creation, documentation, tools and equipment setup, communication plans, and feedback strategies. Discover how proactive pre-onboarding can enhance job performance, increase retention rates, and foster a sense of belonging from day one.

Remote Work Statistics and Insights for 2024

August 13, 2024

The article explores the current statistics for remote work in 2024, covering the percentage of the global workforce working remotely, growth trends, popular industries and job roles, geographic distribution of remote workers, demographic trends, work models comparison, job satisfaction, and productivity insights.