Why is remote work so nice? Let's try to see!
Apply
Lead Data Scientist
Posted 20 days agoViewed
💎 Seniority level: Lead, 5 years
📍 Location: United States
🔍 Industry: Healthcare IT
🏢 Company: Scripta Insights👥 11-50💰 almost 5 years agoMedicalInformation TechnologyHealth Care
🗣️ Languages: English
⏳ Experience: 5 years
Requirements:
- Degree in Data Science, Computer Science, Statistics, or a related field, Master's or PhD preferred.
- Minimum of 5 years of experience in a data science role, with at least 2 years in a leadership position.
- Proficiency in programming languages such as Python, R, or Scala.
- Extensive experience with machine learning frameworks and data visualization tools.
- Strong statistical analysis skills and experience with statistical modeling techniques.
- Excellent communication skills, with the ability to convey complex information clearly to diverse audiences.
- Experience with big data technologies such as Presto/Trino, Spark, Databricks, or similar platforms.
Responsibilities:
- Lead the development and implementation of advanced analytic models and algorithms.
- Define our agentic LLM strategy to streamline operations.
- Collaborate with Engineering teams on improving our drug recommendations, to help our members continue to save money.
- Design, develop, and maintain scalable data pipelines and data infrastructure.
- Build out our data science function, partnering with technology leadership
- Communicate findings and insights effectively to non-technical stakeholders and executives.
- Stay abreast of industry trends and emerging technologies to drive innovation within the team.
- Develop and enforce best practices in data science, including model validation, testing, and reproducibility.
Related Jobs
Apply
🔥 Lead Data Scientist
Posted 5 days ago
🔍 Financial Services
- Degree preferably in Statistics, Mathematics or Computer Science
- 3+ years related experience preferably in Financial Services
- Strong knowledge of statistical analysis software / data analysis experience including modeling and experience in Python and Spark
- Proven track record for leading and executing complex analytical projects and new product development from concept to final delivery.
- Demonstrated ability to communicate ideas and analysis results effectively both verbally and in writing to both a technical and non-technical audience.
- Leverage your analytical skills and experience to evaluate, understand and interpret credit bureau data.
- Optimize existing code and develop new algorithms to improve the processing time of analysis in a true Big Data environment.
- Serve as internal SME in Python and Spark coding on a Big Data platform for an analytic consulting team.
- Communicate with and deliver presentations to end users on model deployment and monitoring results.
- Produce testing to support the implementation of machine learning models into a production.
- Aid in analytical support for high profile modeling, analytical and machine learning engagements and initiatives.
- Support the development of new analytical and data products and services to support business objectives.
- Collect business requirements and make recommendations on machine learning based solutions.
Posted 5 days ago
ApplyApply
🔥 Lead Data Scientist, Marketing Analytics (Remote)
Posted 24 days ago
📍 United States
🧭 Full-Time
💸 160000.0 - 199000.0 USD per year
🔍 Food Technology, Marketing Analytics
🏢 Company: ezCater, Inc
- 5-7+ years experience in data science or related field
- Experience with media mix modeling
- Proficiency in Python or R and SQL
- Knowledge of marketing data science/ML modeling techniques
- Experience with natural and controlled experiment design
- Ability to solve complex problems creatively
- Own Marketing Mix Modeling (MMM)
- Design and implement A/B testing frameworks
- Develop predictive models for marketing impact
- Identify business opportunities through data analysis
- Partner with ML engineering for model integration
- Advise and mentor analysts on complex problems
- Proactively identify opportunities for Advanced Analytics
DockerPythonSQLApache AirflowKubernetesMLFlowData scienceA/B testing
Posted 24 days ago
ApplyApply
🔥 Lead Data Scientist
Posted 29 days ago
📍 India
🧭 Full-Time
🔍 Fintech
- Experience: 8+ years of experience as a Data Scientist, with a proven track record in solving complex problems, particularly in fraud detection or financial crime.
- Machine Learning Expertise: Extensive experience in designing, developing, and deploying machine learning models to detect and mitigate fraud. You should be comfortable translating business challenges into data-driven solutions.
- Working with Large-Scale Data: Proficiency in handling large, tabular datasets, and applying robust techniques for data analysis and model training.
- Advanced Tools and Platforms: Experience with tools such as PySpark, Databricks, AWS, or GCP for processing large datasets, training models, and deploying them at scale.
- Production-Ready Models: Proven ability to deploy models into production environments, optimizing them for performance and scalability, while ensuring they remain effective over time.
- Data & Model Observability: Expertise in monitoring and maintaining the health and performance of models post-deployment to ensure continuous improvement and fraud detection accuracy.
- Fintech & Fraud Detection: Background in the Fintech industry, with specific experience in financial crime and fraud detection, applying data science to solve real-world business problems.
- Collaboration & Communication: Strong interpersonal skills to collaborate effectively with data engineers, machine learning engineers, and product managers in an agile, iterative environment. Ability to communicate complex insights clearly to both technical and non-technical stakeholders.
- Collaborating with the FinCrime team: Work closely to identify and solve fraud detection problems, using data science to drive business decisions and significantly reduce fraudulent activities.
- Translating business requirements: Understand business needs and translate them into data products and models that address specific fraud detection challenges.
- Building and optimizing models: Train machine learning models, optimize hyperparameters, design KPIs, and implement experiments to improve fraud detection accuracy and business outcomes.
- Productionizing models: Work with machine learning engineers and data engineers to deploy models into production, ensuring they are scalable and optimized for real-time fraud detection.
- Adopting new methodologies: Lead the adoption of innovative methods and technologies, continuously improving fraud detection models and data science practices.
- Coaching junior data scientists: Mentor and guide junior team members, setting best practices for model development, optimization, and deployment.
- Being a technical subject matter expert: Serve as a subject matter expert, providing guidance on complex technical concepts related to fraud detection, machine learning, and data science.
AWSPythonSQLData AnalysisGCPMachine LearningAlgorithmsData scienceMentoringData visualizationData modeling
Posted 29 days ago
ApplyApply
🔥 Lead Data Scientist, Analytics
Posted about 1 month ago
📍 United States
🧭 Full-Time
💸 170000.0 - 190000.0 USD per year
🔍 Mental health care
🏢 Company: Alma👥 251-500💰 $130,000,000 Series D over 2 years ago🫂 Last layoff 5 months agoMental HealthMedicalWellnessHealth Care
- You have a Master’s degree in a relevant quantitative field (e.g. data science, statistics, economics, operations research) or equivalent in industry experience.
- You have 4-8 years of experience as a data scientist or product analyst supporting product development.
- You are an expert in SQL.
- You are proficient in either R or Python for data analysis.
- You have extensive experience applying statistical analysis (e.g. hypothesis testing and regression analysis) to draw conclusions from data.
- You have experience designing and analyzing A/B testing experiments.
- You can turn ambiguous business problems into clearly defined data science solutions.
- You can produce exec-ready documents and presentations.
- Generate insights through statistical and causal analysis to inform product strategy and prioritization.
- Proactively identify opportunities to improve client conversion and marketing efficiency.
- Define metrics and OKRs that align team output to company goals.
- Advise senior leadership on key strategic decisions.
- Design, execute, and analyze A/B testing experiments to validate product hypotheses.
- Communicate technical insights effectively to influence decision making.
- Champion a data-driven decision culture.
- Mentor junior data scientists.
PythonSQLData AnalysisData scienceAnalytical SkillsA/B testing
Posted about 1 month ago
ApplyApply
🔥 Lead Data Scientist, Business Analytics
Posted about 2 months ago
📍 United States, Canada, Philippines
💸 168700.0 - 242600.0 USD per year
🔍 Home services marketplace
🏢 Company: Thumbtack👥 1001-5000💰 $275,000,000 Series G over 3 years ago🫂 Last layoff about 2 years agoHome ServicesLocalService IndustryProfessional Services
- BA/BS degree, preferably in Economics, Business, Math, Statistics, or Computer Science.
- 6+ years of experience in a highly analytical role, preferably in tech.
- Proficiency using SQL & Python/R to analyze large data sets.
- Exemplary analytical problem solving skills, including solid statistics foundation, strong business judgment, ability to navigate ambiguity, and the ability to identify and synthesize insights from analysis.
- Ability to work with company executives to understand the company’s business needs and drive decisions.
- Strong communicator, attentive listener, and compelling explainer.
- Define, monitor, and report on the key metrics that measure Thumbtack’s success.
- Lead business performance analysis and reporting to inform leadership of emerging risks and opportunities.
- Conduct deep dive analysis to answer key questions that are critical to Thumbtack’s future strategy.
- Support and improve company revenue forecasting model, and forecasting/planning process.
- Partner effectively with teams across the company, including Product, Engineering, Marketing, Operations, Finance, as well as Thumbtack’s leadership team.
- Contribute to our team and company data culture through peer collaboration, training, coaching, and more.
PythonSQLData AnalysisData visualization
Posted about 2 months ago
ApplyApply
🔥 Lead Data Scientist
Posted 4 months ago
🧭 Full-Time
🔍 Software Development
- 7+ years in Machine Learning, Data Science, and backend development.
- Advanced foundations in ML and statistical methodologies.
- Strong experience in supervised learning, including gradient boosting and handling high-cardinality categorical data.
- Practical experience with semi-supervised and unsupervised learning techniques.
- Proficiency in exploratory data analysis and creative problem-solving for dataset collection and performance estimation in the absence of labeled data.
- Strong expertise in real-time ML service development, including challenges like real-time inference and model-to-service integration.
- Excellent coding skills with expertise in SQL and general software engineering tools (Git, CI/CD pipelines, IDEs, shell scripting).
- Ability to create MVP real-time web services from ML models.
- Develop data-driven algorithms for Fingerprint Pro Identification Service, applying ML techniques to process raw, noisy, and unlabeled data to extract insights about browsers and devices.
- Lead the design and implementation of supervised, semi-supervised, and unsupervised learning approaches to improve our identification capabilities.
- Mentor team members in machine learning, data science, and analytics, enhancing the team's technical expertise.
- Conduct exploratory data analysis to investigate ad-hoc questions and address anomalous data.
- Design experiments and solutions for ML-related engineering challenges like real-time model inference and training pipeline automation.
- Help build an engineering-focused, data-driven culture across the team by sharing tools and effective approaches to data science.
Software Engineering
Posted 4 months ago
ApplyApply
🔥 Lead Data Scientist
Posted 4 months ago
📍 LATAM
🔍 Data Science Consultancy
- Bachelor’s degree in a related field or equivalent experience; advanced degree (MS) preferred.
- 5+ years professional experience in Data Science.
- Demonstrated ability to lead and mentor data science teams.
- Proficiency in SQL, Python, and Jupyter Notebooks.
- Experience with Google Cloud Platform (GCP) or similar cloud platforms.
- Expertise in causal inference, A/B testing, and classification modeling.
- Strong data visualization and storytelling skills.
- Strong problem-solving skills and ability to handle ambiguity.
- Work with practice leaders and clients to understand business problems, industry context, data sources, risks, and constraints.
- Lead customer behavior analysis focusing on identifying trends, customer segments, and sales channel performance.
- Analyze large datasets using SQL and Python to ensure accurate insights.
- Design and implement A/B testing, utilizing causal inference and classification modeling.
- Communicate findings through visualizations and storytelling tailored to stakeholders.
- Guide and mentor junior analysts.
LeadershipPythonSQLData AnalysisGCPData scienceAnalytical SkillsProblem SolvingData visualizationA/B testing
Posted 4 months ago
ApplyApply
🔥 Lead Data Scientist - BA
Posted 4 months ago
📍 Latin America
🧭 Contractor
🔍 Software outsourcing
🏢 Company: Teravision Technologies👥 251-500💰 over 13 years agoAndroidiOSMobile AppsInformation TechnologySoftware
- Demonstrated experience in AI/ML model development and deployment, especially on Azure/Microsoft platforms.
- Proficiency in Python, R, SQL, and relevant ML technologies.
- Experience with cloud-based AI tools, such as Azure Machine Learning, Cognitive Services, and Databricks.
- Familiarity with data visualization tools such as Power BI or Tableau.
- Previous experience in .Net Core, C#, SQL Server type of project is a plus.
- AI-Azure services knowledge is a must.
- Ability to work with clients and stakeholders, identify business needs, and translate them into effective technical solutions.
- Self-starter, motivated, organized, and able to meet goals independently.
- Personable and extroverted, comfortable in client-facing roles.
- Strong analytical and problem-solving skills to tackle complex integration challenges.
- Advanced English communication skills are a must.
- Bachelor’s Degree in Data Science, Computer Science, Statistics, or a related field or equivalent work experience.
- Lead the development and implementation of AI models, using Azure/Microsoft platforms.
- Manage the complete project lifecycle, ensuring timely and high-quality delivery that aligns with client expectations.
- Support pre-sales efforts by sharing insights, preparing proposals, and providing technical guidance.
- Advise clients on AI strategies and best practices to maximize the impact of AI projects.
PythonSQLMachine LearningTableauAzureData science.NET.NET coreCommunication SkillsProblem-solving skillsEnglish communication
Posted 4 months ago
ApplyRelated Articles
Posted 7 months ago
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?
Posted 7 months ago
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.
Posted 7 months ago
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.
Posted 7 months ago
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.