Benefits:

• Fully Remote Working Environment

• Unlimited Paid Leaves

• Co-working Allowance

• Medical Insurance

• Grow & Learn by Getting Things Done

Experience Requirements:

• Min experience in Market Research (2 years - preferably quantitative) or Min experience in Research (4 years - preferably quantitative)

Other Requirements:

• Research Design

• Data Analysis

• Technical Writing

• Project Management

• Relationship management

• Communication & interpersonal skills

• Problem solving

• Fluency in English

• Teaching experience (a plus)

• Experience working in a research agency (a plus)

• Startup experience (a plus)

• Basic knowledge working with CRM (preferably Hubspot) (a plus)

• Experience with research or data analytics software (a plus)

• Academic qualifications that cover quantitative research, with qualitative research being an added bonus (a plus)

• Fluency in Malay or Mandarin (a plus)

Responsibilities:

• Ensuring clients are successful in achieving their research objectives by guiding them through research design and data analysis that will provide them accurate and actionable data.

• Providing in-person, written and in-app guidance to clients, enabling them to conduct their research independently.

• Developing systems and processes to maintain and track client satisfaction, providing them with helpful guidance in a timely manner.

• Building & maintaining relationships with past and current clients, to enable us to better identify and be able to assist with their future research needs.

Benefits:

• competitive salary and benefits package

• opportunity to work on cutting-edge AI projects

• collaborative and supportive work environment

• opportunity to participate in conferences and workshops

• opportunity to participate in Tech Talks (internal training and seminar sessions)

Experience Requirements:

• minimum of 4 years of experience in data science

Other Requirements:

• Skilled in Python with strong familiarity with data science libraries like NumPy, pandas, and scikit-learn

• Proficient in SQL for effective data management and querying

• Strong skills in creating data visualizations

• Excellent written and verbal communication skills

• Excellent problem-solving capabilities

Responsibilities:

• Develop and implement scalable models and analytics solutions to address real-world challenges

• Translate business requirements into data-driven insights and actionable goals

• Optimize data pipelines to enhance data processing and analysis capabilities

• Design automated processes for data analysis and report generation

• Ensure seamless integration of data solutions within client environments

Benefits:

• Profit Sharing

• Generous PTO

• Work from Anywhere

• Advanced Training

• Modern Tech

Benefits:

• Competitive salary based on your experience

• You may work at our office (Luxembourg, Romania, France/Paris), or even from home

• Full coverage of operational costs

• Full-time employment

Education Requirements:

• Bachelor or Master Degree in Computer Science, Mathematics, Statistics, Artificial Intelligence, Data Science, Machine Learning or related fields required

• Graduated AI, Data Science, ML, NLP, Statistics courses are considered to be a plus

Experience Requirements:

• Experience with Machine Learning and NLP, and with developing production ML and / or NLP systems

Other Requirements:

• Proficiency with the Python programming language (minimum 4 years)

• Proficiency with Python and basic libraries for machine learning and data manipulation such as scikit-learn and pandas

• Proficiency with NLP tools and libraries such as NLTK, spaCy, fastText

• Proficiency with SQL

Responsibilities:

• Using ML and NLP techniques to develop new application components or to improve the existing ones

• Integrate the developed application features with the rest of the application

• Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress

• Managing available resources such as hardware, data, and personnel so that deadlines are met

Benefits:

• Competitive compensation

• Medical, Vision and Dental coverage

• Flexible work environment and time-off policy

• 401k

• Company events

Education Requirements:

• Bachelors/Masters/PhD degree in Statistics, Mathematics or Computer Science, or another quantitative field

Experience Requirements:

• 8+ years of industry experience as a data scientist. For PhD degree holders, the minimum years of required experience as a data scientist is 6 years.

• 1+ years of management experience

Other Requirements:

• You have strong business sense, and are strong at defining good product KPIs/guardrail metrics, dashboarding and analysis of raw data to derive strategic insights.

• You are familiar with BI visualization tools such as Sigma, Metabase, Tableau or Looker.

• You are proficient in SQL and the modern data stack (e.g. dbt pipelines for ETL/ELT).

• You are proficient in Python.

• You have experience in writing source-controlled code for pipelines and internal tools for data-oriented decision making.

• You are strong at statistics. You have experience in applying these skills into tangible improvements in products, internal tools and processes using A/B testing and non-experimental methods.

• You are concise and precise in written and verbal communication. Technical documentation is your strong suit.

Responsibilities:

• Define and build data assets, e.g. KPI definitions, data pipelines and dashboards, to measure the performance of AI-powered assistant products for knowledge workers.

• Identify opportunities to improve these KPIs, and influence cross functional teams to incorporate associated changes into their roadmaps.

• Create and maintain quantitative frameworks and methodologies, e.g. bring more rigor into experiment analyses, use statistical modeling to identify leading indicators of user growth and engagement.

Benefits:

• Competitive compensation

• Medical, Vision and Dental coverage

• Flexible work environment and time-off policy

• 401k

• Company events

Education Requirements:

• Bachelors/Masters/PhD degree in Statistics, Mathematics or Computer Science, or another quantitative field

Experience Requirements:

• 5+ years of industry experience as a data scientist. For PhD degree holders, the minimum years of required experience as a data scientist is 2 years.

• You have strong business sense, and are strong at defining good product KPIs/guardrail metrics, dashboarding and analysis of raw data to derive strategic insights.

• You are familiar with BI visualization tools such as Sigma, Metabase, Tableau or Looker.

• You are proficient in SQL and the modern data stack (e.g. dbt pipelines for ETL/ELT).

• You are proficient in Python.You have experience in writing source-controlled code for pipelines and internal tools for data-oriented decision making.

Other Requirements:

• You are strong at statistics. You have experience in applying these skills into tangible improvements in products, internal tools and processes using A/B testing and non-experimental methods.

• You are concise and precise in written and verbal communication. Technical documentation is your strong suit.

Responsibilities:

• Define and build data assets, e.g. KPI definitions, data pipelines and dashboards, to measure the performance of AI-powered assistant products for knowledge workers.

• Identify opportunities to improve these KPIs, and influence cross functional teams to incorporate associated changes into their roadmaps.

• Create and maintain quantitative frameworks and methodologies, e.g. bring more rigor into experiment analyses, use statistical modeling to identify leading indicators of user growth and engagement.

Benefits:

• Competitive compensation

• Medical, Vision and Dental coverage

• Flexible work environment and time-off policy

• 401k

• Company events

Education Requirements:

• Bachelors/Masters/PhD degree in Statistics, Mathematics or Computer Science, or another quantitative field

Experience Requirements:

• 6+ years of industry experience (4+ for Masters degree holders, 3+ for PhD degree holders).

• You are concise and precise in written and verbal communication. Technical documentation is your strong suit.

• You are strong at defining good product KPIs/guardrail metrics, dashboarding and analysis of raw data to derive strategic insights.

• You are proficient in SQL and the modern data stack (e.g. dbt pipelines for ETL/ELT).

• You have experience in writing source-controlled code for pipelines and internal tools for data-oriented decision making.

Other Requirements:

• You’re strong in statistics and/or machine learning. You have experience in applying these skills into tangible improvements in products, internal tools and processes.

• You are proficient in Python.

Responsibilities:

• Define and build data assets, e.g. KPI definitions, data pipelines and dashboards, to measure the performance of AI-powered assistant products for knowledge workers.

• Identify opportunities to improve these KPIs, and influence cross functional teams to incorporate associated changes into their roadmaps.

• Create and maintain quantitative frameworks and methodologies, e.g. bring more rigor into experiment analyses, use statistical modeling to identify leading indicators of user churn & retention.

Education Requirements:

• PhD in Artificial Intelligence or Machine Learning

Other Requirements:

• Research / published papers in Auto ML, Neural Architecture Search, Personalization, or Forecasting

• Experience publishing at top conferences

• Able to write code and ideate with the product team

Responsibilities:

• Coming up with new techniques in unsupervised learning, dataset augmentation and deep reinforcement learning that can be applied to automating various parts of the AI development workflow

Experience Requirements:

• passion for adopting new research, tinkering with open source, and unlocking new creative possibilities with AI

Other Requirements:

• LLM Training / Inference

• Pytorch / CUDA

• Optimization (Pruning, Distillation, Kernel Fusion, etc.)

Education Requirements:

• Master’s degree in data analytics, business analytics, or a closely related field

Experience Requirements:

• 1 year of relevant data analytics experience

Other Requirements:

• Stats / ML

• A/B Testing

• Product Analytics

• SQL / Python

Responsibilities:

• Formulate hypotheses and apply rigorous analytical methodologies to validate them

• Use statistical analysis, ML, and data mining to uncover product insights

• Implement predictive models to guide product direction

• Define KPIs and develop dashboards to track performance

• Conduct A/B testing and experimental methods to measure feature impact

Benefits:

• Competitive Salary

• WeWork membership for remote employees

• Annual Company Week Off (in addition to Vacation Policy)

• Birthday Off (in addition to Vacation Policy)

• Monthly fitness stipend

Experience Requirements:

• Attention to Detail

• Understanding of E-commerce Workflows

• Tech Savvy

• Communication Skills

• Good Time Management

Other Requirements:

• Background in E-commerce Customer Service (Preferred)

Responsibilities:

• Review and label e-commerce customer service conversations and policies with high accuracy.

• Collaborate with the AI and product teams to refine and optimize data labelling guidelines.

• Take ownership of data quality to improve AI model training.

• Work in collaboration with AI engineers to identify trends and nuances in customer service data that can be leveraged to fine-tune and improve our AI models.

• Manage the quality control process for labelled data, using a variety of modern tools and platforms for data processing and management, from advanced spreadsheets to AI-driven data labeling tools and project management systems.

Benefits:

• Entrepreneurial and inclusive culture

• Excellent health coverage

• Four weeks paid vacation

• Catered lunches twice a week over machine learning talks

• Opportunities to collaborate with faculty at the Vector Institute

Education Requirements:

• BSc+ in Computer Science, Math, Physics, or similar

• PhD or Master’s degree in Computer Science, Statistics, Mathematics, Engineering or a related field

Experience Requirements:

• 3+ Years of industry experience as a Software Engineer leading the development of features

• Experience with building and scaling data-intensive software.

• 2+ years of research experience with publication record

• 2+ years of extensive programming experience, 1+ year experience of building machine learning production system

Other Requirements:

• Experience with building a library or a framework.

• Experience with Big Data technologies and frameworks including but not limited to Spark, Cassandra, Kafka.

• Experience with Microsoft Azure

• Comfortable with statistics.

• Knowledge of machine learning and deep learning.

• Knowledge of distributed systems.

• Strong background in machine learning and deep learning

• Proven track record of applying machine learning to solve real-world problems

• Depth of experience in relevant ML research disciplines

• Hands on experience in software systems development

• Experience with one or more of Pytorch, Tensorflow, Jax, or comparable library

• Experience with Spark, SQL, or comparable database systems

• Experience using GPUs for accelerated deep learning training

• Familiarity with cloud computing systems like Azure or AWS

• Strong communication, business acumen and stakeholder management competencies

• Strong technical skills: machine learning, data engineering, MLOps, cloud solution architecture, software development practices

• Strong coding proficiency: python, R, SQL and / or Scala, cloud architecture

• Certified Scrum Product Owner and / or Certified Scrum Master or equivalent experience

• Familiarity with cloud solution architecture, Azure a plus

• Solid knowledge of applied Machine Learning, Deep Learning, Large Language Models

• Experience with developing MLOps CI/CD pipelines for deploying AI/ML models

• Solid cloud experience with Azure or AWS and cloud AI/ML services such as Databricks, Kubernetes, docker and container orchestration, Azure Machine Learning, Azure Data Factory

• Strong experience with PySpark for big data processing and PyTorch for deep learning model serving

• Expert coder with Python, Java, or Scala

• Experience with RAG, LLM fine tuning, LLM serving

• Practical expertise in performance tuning, bottleneck problems analysis, and troubleshooting

• Knowledge of cloud engineering

• Self-motivated and demonstrated ability to take independent action to delivery results.

• Highly developed critical thinking, analytical and problem-solving skills

• Strong verbal and written communication skills, with the ability to work effectively across teams

Responsibilities:

• Own and ship product features that enable ML engine capabilities.

• Work with product owners and tech leads to design, ship, and refine significant components of the product.

• Work with scientists and MLOps teams to maintain and service the product.

• Translate broad business problems into sharp data science use cases, and craft use cases into product visions

• Own machine learning products from vision to backlog; prioritizing features and defining minimum viable releases; maximizing the value your products generate, and the ROI of your pod

Benefits:

• Entrepreneurial and inclusive culture

• Excellent health coverage

• Four weeks paid vacation

• Catered lunches twice a week over machine learning talks

• Opportunities to collaborate with faculty at the Vector Institute

Education Requirements:

• PhD or Master’s degree in Computer Science, Statistics, Mathematics, Engineering or a related field

Experience Requirements:

• 2+ years of research experience with publication record

• Proven track record of applying machine learning to solve real-world problems

Other Requirements:

• Depth of experience in relevant ML research disciplines

• Hands on experience in software systems development

• Experience with one or more of Pytorch, Tensorflow, Jax, or comparable library

• Experience with Spark, SQL, or comparable database systems

• Experience using GPUs for accelerated deep learning training

• Familiarity with cloud computing systems like Azure or AWS

Responsibilities:

• Join a world-class team of machine learning researchers with an extensive track record in both academia and industry.

• Research, develop, and apply new techniques in deep learning to advance our industry leading products.

• Work with large-scale, real-world datasets that range from banking transactions, to large document collections.

• Collaborate closely with our engineering team in a fast-paced startup environment and see your research deployed in production with very short turnaround.

Education Requirements:

• PhD in Artificial Intelligence or Machine Learning

Other Requirements:

• Research / published papers in Auto ML, Neural Architecture Search, Personalization, or Forecasting

• Experience publishing at top conferences

• Able to write code and ideate with the product team

Responsibilities:

• Coming up with new techniques in unsupervised learning, dataset augmentation and deep reinforcement learning that can be applied to automating various parts of the AI development workflow

Benefits:

• Competitive salary

• Generous health, dental, and vision insurance

• Flexible working hours

• Flexible vacation time

• Hybrid/Remote friendly work environment

Education Requirements:

• Phd or Master’s level degree in computer science, machine learning, engineering or related fields

Experience Requirements:

• 2-5 years of experience working as a data/AI scientist developing AI models and evaluation of AI/LLM models

• Experience applying both technical and non-technical (policy, ethical, social) approaches to model risk and impact assessments

• Familiarity with requirements contained in AI regulations as well as leading standards and frameworks (EU AI Act, NIST AI Risk Management Framework, ISO Standards, etc)

Other Requirements:

• Excellent organizational and project management skills, including the ability to lead a small team on client-facing projects

• Strong technical, analytical and conceptual problem-solving skills

• Demonstrated experience drafting reports and academic publications

• Team player

• Comfortable in a flexible and evolving environment

• Ability to multitask

Responsibilities:

• Support client model assessment projects from start to finish, including advising on the selection and development of test plans and evaluation metrics suited to the business use case and regulatory requirements

• Play a lead role in drafting model assessment reports for clients, including addressing the broader compliance and/or business impacts of assessment technical findings

• Develop and document assessment team standard operating procedures with a view to improving project efficiency and customer satisfaction

• Serve as one of the main points of contact for technical questions related to model assessment approaches and findings

• Work with the Chief Technology and Product Officer and assessment team to identify state-of-the-art techniques, methods and tools for model testing, evaluation and validation of AI/ML systems, including generative AI

Benefits:

• 401K and AD&D

• Healthcare

• Global Exchange Program

• Work from anywhere

• Employee stock options

Education Requirements:

• MSc degree in Computer Science or a related technical field or equivalent practical experience

Experience Requirements:

• 3+ years of proven experience in delivering production level ML solutions

• Experience with time series modeling, supervised and unsupervised learning

• Experience with Causal Inference

Other Requirements:

• Strong business understanding and high execution mentality

• Deep understanding of ML theory and the math behind the models

• Building interpretable and explainable solutions

• Proficiency in Python, relational and NoSQL databases, Git

• Knowledge of data management and visualization techniques

• Technologically diverse background and ability/willingness to learn new things quickly

• Strong engineering and communication skills

• Advantage: experience with Multi-Arm Bandits

• Advantage: experience with LLMs

Responsibilities:

• Own the Data Science deliverables across our various products

• Conduct exploratory research on structured and unstructured data

• Be involved in team architectural discussions

• Research, build and deploy ML models in different domains

• Create technical specifications and project documentation

Benefits:

• Competitive compensation package

• Employee options awards

• Flexible working environment

• Growth opportunities

Experience Requirements:

• 3+ years as a Data Scientist or ML Engineer

Other Requirements:

• Fluency in Python

• Knowledge of data structures and algorithms

• Experience with Apache Spark

• Good analytical and problem-solving skills

Responsibilities:

• Developing new data-science/ML functions

• Maintaining and improving existing codebase

• Collaborating with other teams

• Supporting marketing, sales, and clients

• Mentoring junior data scientists

Benefits:

• We're completely remote.

• Competitive base salary and stock option plan.

• We have full health insurance for both Canadian and US residents.

• We offer unlimited vacation.

• Flexible hours - create your most productive work schedule

Other Requirements:

• Exceptional analytical reasoning and problem-solving skills, with a profound understanding of data science, machine learning, and statistical principles

• Advanced proficiency in Python for data manipulation, analysis, and model development

• Comprehensive knowledge of machine learning algorithms, especially LLMs and transformers, with expertise in metric spaces and vectorization techniques

Responsibilities:

• Data Profiler Function Development

• Embedding Model Deployment Contribution

• LLMs Performance Optimization

• Multidimensional Analysis Development Support

Benefits:

• We're completely remote.

• Competitive base salary and stock option plan.

• We have full health insurance for both Canadian and US residents.

• We offer unlimited vacation.

• Flexible hours - create your most productive work schedule

Other Requirements:

• Demonstrate exceptional analytical and problem-solving abilities, grounded in a solid understanding of data science and statistical principles

• Proficient in Python, particularly for data manipulation and analysis

• Basic knowledge of LLMs, especially transformers, and an understanding of LLM training and fine-tuning principles

Responsibilities:

• Dataset Optimization

• Data Profiling Assistance

• Model Development Support

• Multidimensional Analysis Support

Responsibilities:

• develop

• test

• apply AI-based drug-discovery platform