捆绑SM社区

Please stay tuned for new job openings.

As a Business Development Consultant at the DataSphere Lab, you will drive business development initiatives by understanding lab objectives, creating strategic business plans, exploring new partnerships, and crafting sales and marketing strategies to promote the lab鈥檚 services.

As a Marketing & Promotion Consultant at the DataSphere Lab, you will develop marketing assets (posters, presentation decks, one-pagers), contribute to promotional strategies, and engage with clients and stakeholders to drive effective communication and outreach efforts.

A Content Developer in website development creates and builds websites that clearly communicate our mission, services, and value, enhancing its online presence by tailoring information to users' interests. They also produce marketing assets, such as overviews, one-pagers, brochures, and other materials that succinctly express our service offerings. In the social media sphere, the Content Developer creates engaging content to connect with online communities, fostering an active social media presence to raise awareness of the DataSphere Lab's offerings and achievements.

Part-time opportunities for Content Developer at the DataSphere Lab will be posted here as they become available.

The Content Writer is responsible for conducting extensive research to aid in the Grant writing process. This role requires good research skills, curiosity and a keen understanding of grant application processes and guidelines.

The Event Planner is responsible for planning, organizing, and managing events such as workshops, seminars, and conferences that promote the lab's activities and services. This includes coordinating logistics, liaising with speakers, and ensuring smooth execution of events. The event planner must have strong organizational skills, the ability to multitask, and a keen interest in creating engaging and informative events for the lab's audience.

Part-time opportunities for Event Planner at the DataSphere Lab will be posted here as they become available.

The Marketing Attribution Modeler is a part-time role focused on Marketing Mix Modeling (MMM), which involves using statistical analysis on sales and marketing time series data to estimate the impact of various marketing tactics on sales. The role is pivotal in analyzing marketing effectiveness and guiding strategic advertising decisions through advanced statistical modeling techniques.

Part-time opportunities for Marketing Attribution Modeler at the DataSphere Lab will be posted here as they become available.

We are looking for a highly skilled Synthetic Data Engineer to join our team and lead the development of our Synthetic Data as a Service (SDaaS) offering. The successful candidate will be responsible for building scalable solutions to generate high-quality synthetic data that mirrors real-world datasets, ensuring privacy preservation, while maintaining statistical and structural integrity. You will collaborate with data scientists, machine learning engineers, and product teams to design, implement, and maintain our synthetic data pipelines.

This is a key role in our DataSphere Lab, where we push the boundaries of data innovation to meet the growing demand for privacy-safe, high-utility synthetic data across various industries.

Key Responsibilities:

• Design and Develop SDaaS Solutions: Lead the architecture and implementation of scalable synthetic data generation frameworks, ensuring flexibility for various industries and use cases.
• Data Modeling and Generation: Utilize machine learning, generative models, and statistical methods to create synthetic datasets that mimic real-world data distributions.
• Quality Assurance: Develop evaluation frameworks to measure the accuracy, utility, and representativeness of synthetic data in comparison to real datasets.
• Client Collaboration: Work closely with clients to understand their synthetic data needs and help them integrate synthetic data solutions into their workflows.
• Automation and Scalability: Build automation tools and processes for creating, managing, and distributing synthetic datasets, ensuring scalability as part of a DaaS offering.

Required Skills & Qualifications:

• Technical Expertise:
  • Strong proficiency in programming languages such as Python, R, or Java.
  • Experience with machine learning and statistical modeling techniques.
  • Familiarity with synthetic data generation frameworks, libraries, and tools.
  • Understanding of data privacy techniques, including differential privacy, anonymization, and pseudonymization.
  • Experience with cloud platforms (e.g., AWS, GCP, Azure) and deploying DaaS solutions.
  • Knowledge of SQL and NoSQL databases for data storage and retrieval.
• Analytical Skills:
  • Ability to work with primarily structured data.
  • Strong data analysis and data visualization skills, including tools such as Pandas, Matplotlib, or Seaborn.
  • Experience in validating and assessing the quality and utility of synthetic data against real datasets.
• Soft Skills:
  • Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
  • Ability to work collaboratively across cross-functional teams and client-facing environments.
  • Problem-solving mindset, able to innovate and find solutions to complex data challenges.

Preferred Qualifications:

• Master鈥檚 or PhD in Computer Science, Data Science, Statistics, Machine Learning, or a related field.

Why Join Us?

• Work on the cutting edge of data science and privacy.
• Opportunity to build a new product from the ground up and shape the future of synthetic data services.
• Collaborative, innovative team environment with a focus on career growth.

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We are seeking a highly skilled and motivated Programmer with a specialty in web/applications to join our dynamic team to work on a project for a client which is a leader in the aviation industry.

We are building a platform/website which will allow the company to manage its product related documents and business processes, and leverage AI and machine learning to improve the process efficiency and gain insights from the data. You will be part of a team rebuilding/redesigning a bespoke application for the client to improve one of their core processes, and this tool will support research initiatives with the client and the University.

You will be working with a Professor at the Desautels Faculty of Management, 捆绑SM社区. You do not always need to be on campus to work (time and place are flexible).

Key Responsibilities:

1. Design and Develop a front-end Application using react/angular as frontend and node.js (or .NET) as backend.
2. Design and Develop a database to store and manage the documents as well other data required for the website/platform other database and web programming tasks. Most likely we will use relational database like mySQL. But we may also examine if a noSQL database like MongoDB may be better for the given business needs.

Required Skills:

1. Proficient in HTML, CSS, JavaScript, Databases (mySQl and/or mongoDB); React framework; Node.js.
2. Should have good knowledge of data structures and algorithms

The Ideal candidate will have proficiency in both front and back-end development. However, even if you do not meet both requirements, you can still apply if you have excellent command of a programming language, are willing to learn and strongly believe that you can fulfill the job requirements.
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We are seeking a motivated and detail-oriented Industry Project Analyst to contribute to the development of an innovative software solution that enables buyers to conduct market research in specific ecosystems or commodity purchases. The goal is to build a tool that identifies companies selling specific products based on various criteria (e.g., product type, geographic distance, local availability) while providing insights into supplier pedigrees, sustainability practices, and compliance with regulations. This tool will empower users to understand the supplier landscape before initiating procurement processes, offering a blend of functionalities inspired by platforms like Tealbook and Dun & Bradstreet.

Key Responsibilities:

• Market Research Tool Development:
  • Collaborate with the project team to design and prototype a user-friendly software solution.
  • Develop features to identify and display supplier companies based on search criteria like product type, proximity, and local availability.
• Supplier Insights:
  • Enable the analysis of company pedigrees, including their connections to other organizations, using identifiers such as NEQ numbers.
• Data Integration & Analysis:
  • Identify and source relevant data feeds (e.g., public tenders, SEAO, contracts).
  • Build functionalities for basic and advanced analytics, helping users understand market trends and supplier dynamics.
• User-Centric Design:
  • Collaborate with end-users to refine search criteria and improve the tool鈥檚 interface.
  • Test and iterate on the tool to ensure it meets user needs effectively.
  • Propose and implement features to evaluate suppliers based on 鈥済reen鈥� practices or other corporate social responsibility metrics.
  • Incorporate visualizations and reporting features for actionable insights.

Required Skills and Qualifications:

• Current enrollment in a relevant field of study (e.g., computer science, data science, supply chain management, business analytics, or related fields).
• Strong analytical and problem-solving skills.
• Proficiency in programming languages (e.g., Python, JavaScript) and familiarity with database management.
• Experience or interest in data visualization tools and market research methodologies.
• Added benefit if candidate possesses the following (But not required):
  • Knowledge of procurement processes and supplier ecosystems.
  • Familiarity with tools like Tealbook, Dun & Bradstreet, or SEAO.
  • Understanding of sustainability regulations and practices in supply chains.
  • Interest in user interface (UI) and user experience (UX) design principles.
• Soft Skills:
  • Independent worker and strong communication and teamwork abilities.
  • Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders.
  • Collaborative mindset, with experience working on cross-functional teams and with external clients.
  • Problem-solving abilities, with a focus on delivering innovative solutions to client needs.

Why Join Us?

• Opportunity to work on cutting-edge NLP projects in the consumer goods sector.
• Collaborate with a talented and multidisciplinary team of data scientists, engineers, and product managers.
• Shape the future of how companies use customer feedback to improve products and services.
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We are seeking a highly skilled and motivated Data Scientist with a specialty in image recognition to join our dynamic team. The ideal candidate will have a strong background in machine learning algorithms, cloud computing, and a passion for the intersection of art and technology. You will be working with a small team on a direct Client project. This client is in the Modern Art industry and looking to use AI in various use cases.

Key Responsibilities:

• Develop, implement and use market-available image recognition models and algorithms.
• Collaborate with cross-functional teams to integrate image recognition capabilities into various projects.
• Manage and analyze large datasets of images to identify patterns and insights, and conduct classification analysis
• Stay abreast of the latest developments in machine learning and image recognition.
• Present findings and recommendations to stakeholders and academic peers.

Required Skills:

• Proficiency in Python and experience with version control systems such as Git.
• Strong knowledge/familiarity of image recognition algorithms, including but not limited to:
  • Convolutional Neural Networks (CNNs)
  • Residual Networks (ResNets)
  • Recurrent Neural Networks (RNNs)
  • Generative Adversarial Networks (GANs)
• Familiarity with the three main cloud providers:
  • Microsoft Azure
  • Amazon Web Services (AWS)
  • Google Cloud Platform (GCP)
• Familiarity with these popular cloud tools:
  • Google Cloud Vision API
  • Amazon Rekognition
  • Microsoft Azure AI Vision
• Familiarity with commercial recognition images tools like:
  • SuperAnnotate
  • DeeepSignals
  • Vue.ai
  • V7
• A keen eye for the artistic aspects of data visualization and image processing.
• Experience with image preprocessing, cleaning, and augmentation techniques.
• An appreciation for Art/Design would be an asset
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We are looking for an experienced Marketing Data Analyst to join our team and lead the development of Marketing Mix Models (MMM) and Multi-Touch Attribution (MTA) analysis using the Amazon Marketing Cloud (AMC) platform. In this role, you will design and execute marketing analytics projects that provide deep insights into the effectiveness of various marketing channels and campaigns, helping our clients optimize their marketing spend and ROI.

The ideal candidate will have expertise in marketing analytics, data science, and has familiarity or can learn the Amazon Marketing Cloud ecosystem. You will work closely with our marketing, data science, and client success teams to create data-driven strategies that deliver actionable insights and drive business growth.

Key Responsibilities:

• Develop Marketing Mix Models (MMM): Design and implement MMM frameworks to quantify the impact of marketing activities across multiple channels (e.g., Amazon Ads, social media, display ads, etc.) on business outcomes such as sales and conversions.
• Multi-Touch Attribution (MTA): Create and refine MTA models to analyze the customer journey across multiple touchpoints, attributing credit to each channel based on its contribution to the final conversion.
• Amazon Marketing Cloud (AMC) Expertise: Leverage the Amazon Marketing Cloud platform to access, aggregate, and analyze first-party data to understand marketing performance across Amazon-owned and external channels.
• Optimization of Marketing Spend: Provide recommendations to clients on how to optimize their marketing budget and resource allocation based on the insights from MMM and MTA models.
• Client Collaboration: Work closely with clients to understand their business objectives and tailor marketing analysis to meet their specific needs. Present findings and recommendations in a clear, actionable format.
• Data Visualization: Basic visualization to display MMM and MTA results and understand the impact of marketing decisions in real-time.
• Model Validation and Continuous Improvement: Plan to evaluate and validate the accuracy of the MMM and MTA models after client handoff, iterating and refining them to improve predictive performance and business relevance.

Required Skills and Qualifications:

• Technical Expertise:
  • Experience building and deploying Marketing Mix Models (MMM) and Multi-Touch Attribution (MTA) models in real-world environments.
  • Strong proficiency in data science and machine learning techniques, particularly in marketing analytics, using languages such as Python, R, or SQL.
  • Experience with the Amazon Marketing Cloud (AMC) platform, including navigating the platform and querying datasets using SQL.
  • Familiarity with cloud platforms (AWS, GCP, Azure) would be an asset.
• Marketing Knowledge:
  • Good understanding of digital marketing channels (e.g., Amazon Ads, Google Ads, Facebook Ads), their role in the customer journey, and their measurement methods.
  • Familiarity with different attribution models (e.g., last-click, linear, time-decay) and their application in MTA will be an asset.
  • Knowledge of media buying and advertising strategies, including programmatic advertising, search, and social campaigns will be an asset.
• Analytical Skills:
  • Ability to apply statistical methods to model marketing performance and ROI for different channels and touchpoints.
  • Strong skills in analyzing data across multiple sources and identifying actionable insights to optimize marketing strategies.
• Soft Skills:
  • Strong and reliable communication skills
  • Strong collaboration skills to work with cross-functional teams, including data engineers, marketers, and client account managers.
  • Detail-oriented with the ability to manage multiple projects and deliver high-quality results in a fast-paced environment.

Preferred Qualifications:

• Bachelor鈥檚 or Master鈥檚 degree in Data Science, Marketing Analytics, Statistics, Computer Science, or a related field.
• Experience working with major e-commerce platforms like Amazon and analyzing marketing data across a variety of digital channels would be an asset.
• Familiarity with advanced marketing attribution techniques such as probabilistic or data-driven attribution would be an asset.
• Previous experience working with marketing agencies or consumer goods companies would be an asset.

Why Join Us?

• Opportunity to work at the intersection of data science and marketing in a rapidly evolving field.
• Collaborate with a dynamic and innovative team that values creativity and data-driven decision-making.
• Competitive compensation package, with ample opportunities for professional growth and development.
• Play a critical role in shaping the future of marketing analytics for leading consumer goods brands.
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We are seeking an experienced NLP & Sentiment Analyst to join our team and lead a project focused on developing a Ratings and Reviews analysis platform for a major consumer goods client. This role will involve designing and implementing natural language processing solutions to summarize website comments, extracting key insights, entities, and trends from unstructured customer feedback.

The ideal candidate will have strong expertise in NLP techniques, and data analysis, and will play a key role in building tools that translate raw customer reviews into actionable business insights. You will collaborate closely with data scientists, product managers, and the client to develop a robust platform that provides summaries, sentiment analysis, and key entity extraction from consumer reviews.

Key Responsibilities:

• Develop NLP Solutions: Build and deploy models for analyzing customer ratings and reviews, using natural language processing and machine learning techniques.
• Entity Extraction: Design and implement systems to extract meaningful entities such as product features, customer sentiment, and key topics from website comments and reviews.
• Summarization: Create algorithms for generating concise summaries of customer feedback, highlighting trends, key concerns, and product performance based on review data.
• Sentiment Analysis: Implement sentiment analysis models to gauge customer satisfaction and identify areas for improvement in product offerings.
• Client Collaboration: Work with the client and internal teams to ensure the solutions meet business needs, including translating technical insights into actionable recommendations for the client.
• Continuous Improvement: Monitor the performance of models and continuously optimize for accuracy, relevance, and speed.

Required Skills and Qualifications:

• Technical Expertise:
  • Proficiency in natural language processing techniques, including text classification, entity extraction, sentiment analysis, and summarization.
  • Experience with popular NLP libraries and frameworks such as spaCy, NLTK, Hugging Face, etc.
  • Strong programming skills in Python for NLP and data analysis.
  • Experience working with unstructured data and text mining techniques.
  • Experience with cloud platforms (AWS, GCP, Azure) and tools for processing large datasets (e.g., Hadoop, Spark) would be an asset.
• Analytical Skills:
  • Ability to clean, preprocess, and analyze large datasets to extract actionable insights.
  • Experience in developing models for review and feedback analysis, including entity recognition and trend analysis.
  • Familiarity in data visualization using tools.
• Soft Skills:
  • Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders.
  • Collaborative mindset, with experience working on cross-functional teams and with external clients.
  • Problem-solving abilities, with a focus on delivering innovative solutions to client needs.

Preferred Qualifications:

• Bachelor鈥檚 or Master鈥檚 degree or higher in Analytics, Computer Science, Data Science, Linguistics, or a related field with a focus on NLP.
• Experience in the consumer goods sector or e-commerce industry, working on customer experience or product feedback projects would be an asset.
• Experience with data labeling and annotation platforms would be an asset.
• Previous experience working on projects that involve analyzing product reviews, ratings, or social media feedback would be an asset.

Why Join Us?

• Opportunity to work on cutting-edge NLP projects in the consumer goods sector.
• Collaborate with a talented and multidisciplinary team of data scientists, engineers, and product managers.
• Shape the future of how companies use customer feedback to improve products and services.
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We are currently hiring a UX/UI Designer for an SME client project in the Sports and Leisure Retail Space.

Key Responsibilities:

• Develop a Descriptive Analytics Dashboard for the client鈥檚 Sales and Inventory Operations
• Although the tool is yet to be determined, it will likely be in a popular platform like PowerBI, Tableau, Looker etc.
• The role will be more of a design role than a technical role, and you will be able to leverage the DataSphere Lab鈥檚 team for support with data integrations and other technical elements
• Work with our Analytics Strategist to define essential KPIs to display in the dashboard
• You should expect approximately 10-15 hours per week for this project
• Role begins immediately and estimated project completion is 8-12 weeks

Required Skills:

• Completing /recently completed a bachelor's or master's degree in a relevant field such as Business, Analytics, Information Systems or any field that centres on data and or design.
• Excellent Design, problem-solving and analytical skills.
• Strong communication and presentation abilities, with the ability to explain complex concepts to both technical and non-technical stakeholders.
• Ability to work independently and collaboratively in a team environment.
• Strong attention to detail and ability to manage multiple tasks simultaneously.
• Familiarity with analytics, machine learning, artificial intelligence would be an asset but not required
• Familiarity/Passion for sports (in particular Soccer) would be an asset

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