Procurement Data Scientist Jobs

Leading Edge Tech Stack: Experience build products that will be deployed globally on a leading-edge tech stack.

World Class Mentorship and Training: Working with renowned, published leaders and academics in machine learning to further develop your skillsets.

Previous experience (through co-op or internship) as a data scientist preferred

Apply data science expertise in machine learning, statistics, text-mining/NLP, forecasting and optimization to multiple analytics projects.  

Build models, algorithms, simulations, and experiments by writing highly optimized code and using state-of-the art machine learning technologies. 

Work on full-spectrum of activities, from conducting ML experiments to delivering production-ready models. 

Prepare reports for management stating trends, patterns, and predictions using relevant data.

Minimum Years of Experience: 3 in relevant field.

Experience with common data science toolkits such as R, SQL, and Python; familiarity with AI tools is an asset.

Experience with data visualization tools, such as Power BI, Tableau, Qlik Sense, etc.

In-depth knowledge of mathematics and statistics.

Excellent written and verbal communication skills and presentation skills.

Experience working with Machine Learning teams.

You have proven experience as a Data Scientist using experimentation methods and advanced statistical modeling to drive product development.

You have hands-on experience synthesizing insights from data using tools such as Python, R, BigQuery, SQL, Tableau.

Identify the most impactful opportunities for product development based on user needs, and execute on them diligently and resourcefully.

Define the metrics and dashboards we use to measure the health and success of our products.

Mentor and coach data scientists and tackle leadership opportunities within the larger data science community.

Develop and implement state-of-the-art algorithms and models that underpin AI features and capabilities.

Collaborate closely with engineering and product teams to comprehend requirements and translate them into effective AI features.

The candidate should have experience with modern machine learning and data science toolkits such as PyTorch/Tensorflow, Pandas, NumPy, Scikit-learn, Jupyter/Python.

Experience with training transformers, MLOps and tools such as SpaCy and Azure ML is a plus, as is experience with C#

Identify and source relevant structured and unstructured data from various internal and external sources.

Collect, preprocess, and transform data into usable formats, ensuring accuracy, completeness, and quality.

Partner with product managers, engineers, marketers, designers, and operators to translate data insights into decisions and action

Establish metrics that measure the health of our products, as well as rider and driver experience

1-2 years of industry or project experience in solving data science or analytics problems

Experience in programming, especially with data science and visualization libraries in Python or R is helpful

Experience in statistical analysis (experience in online experimentation preferred)

Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners

Establish the life cycle management process for models.

Provide technical mentoring in modeling and analytics technologies, the specifics of the modeling process, and general consulting skills.

Experience in advanced analytics / data science technologies (e.g., machine learning, operations research, statistics, data mining)

Working knowledge of Microsoft Azure and tools in its ecosystem; proficiency in Python or R for data manipulation and analysis.

Experience solving problems with spatial autocorrelation and quantifying uncertainty using probabilistic algorithms is an asset.

Experience with data visualization tools.

Strong experience in data analysis, statistical modeling, and machine learning, with a focus on applying these skills to solve business problems

5+ years of analytics and data science experience or equivalent

Experience leading cross-functional projects and partnering with Product/Engineering/Marketing/Design on strategy and prioritization;

Experience with 0 to 1 products is a huge plus

Apply a diverse set of tactics such as statistics, quantitative reasoning, and machine learning to research and produce insights

Coordinate and solve complex projects that extend beyond the traditional boundaries of product domains, analytics, and data science

Collaborate with cross-functional teams to understand project requirements and develop prototypes that meet those requirements

Test and iterate on prototypes to refine them and ensure they meet project goals and user needs

Document the prototyping process and provide clear instructions and specifications for handoff to development teams

Stay up-to-date with emerging technologies and trends, including machine learning and AI, and proactively identify opportunities for innovation and improvement.

Expertise in software development, hardware engineering, or another relevant field

Proficiency in programming languages such as Python, Java, or C++.

Procure skills and knowledge on Python, Scikit-learn, Pandas, Numpy, Jupyter, PyTorch, Tensorflow, Matplotlib, Docker, AWS.

Basic understanding of Machine Learning concepts, and entry-level Python programming skills.

Applying your Machine Learning and Data Science skills to real practical problems from different industries.

All the candidates will be invited to complete a Skills Review Survey.

A problem solver, someone who enjoys challenges

A passion for learning and self-improvement

The following knowledge & experience is considered an asset:

Capture and interpret business requirements in the form of user stories.

Post-secondary education in Engineering, Computer Science, Mathematics, or Statistics

Experience conducting data analysis with one or more of the following (Power BI, R, Python)

Knowledge of Database Architecture and delivering solutions within Database Systems (SQL & NOSQL)

Advanced knowledge of statistical models

●Experience with relational databases such as PostgreSQL, MySQL, SQL Server, Oracle (PostgreSQL preferred)

●Successfully completed introductory database courses (Database concepts or design) or demonstrated equivalent on the job experience

●Experience writing data processing and ETL scripts (Python preferably)

●Experience with PL/pgSQL and PostGIS

●Experience with cloud providers, Microsoft Azure preferred.

●Experience working on an Agile/Scrum application team.

2. 5-7+ years of working experience as a Data Scientist

3. 5-7+ years of recent and hands-on experience with Python

• Natural Language Processing Experience – preferably demonstrated in recent projects

• Solid SQL skills for querying relational databases (e.g. SQL Server, DB2, MySQL)

• Working experience with machine learning and other AI techniques for strategy design

• Previous experience working in Banking/FI

Strong communication, time management and work organization skills.

Communicate the results and performance of the models to management.

General knowledge of the insurance sector and relevant experience in the area would be an asset.

Three years of experience in the field of advanced statistics, data mining and text mining.

Multi-platform production experience with the following commercial and open-source data mining frameworks: Open-source frameworks: R, Python, GitHub.

Knowledge of data science approaches in understanding the consumer would be an asset.

Knowledge of economics and/or finance and financial markets data

Knowledge and experience with ML Ops, Data Ops, or Dev Ops in general

Salaries are based on qualifications and experience and typically range from $83,500 to $98,235 (job grade 16)

Experience tuning open-source Large Language Models (LLMs) for financial market applications

Knowledge of cloud computing and data science over cloud platforms is a strong asset

Language requirement: English or French essential

Excellent Python & SQL skills, first hand experience working with popular Python libraries such as Pandas, scikit-learn, numpy and Jupyter

Translate business requirements into data models and analysis that will help stakeholders answer key business questions and inform strategic decisions

Get the best out of the team by leveraging their diverse educational backgrounds

Adjusts quickly to changing priorities and effectively manages complexity and change

Has exceptional communication skills and is able to communicate effectively to both technical and non-technical teams

Building a high quality and scalable state-of-the-art data warehouse that powers all decision making

Investigate groups of fraudulent users and efficacy of new signals and detection methods with the aim of enhancing our detection capabilities

Work closely with cross-functional teams of data and ML engineers, analysts, user researchers, product managers and designers

You have a minimum of 4 years work experience with an emphasis on investigative data analysis, anomaly detection, and data pipelines

You have a deep understanding of numbers, a strong interest in research, and an experienced and mature business sense

You have expert level SQL and intermediate level Python skills

Strong communication and data presentation skills (such as Tableau and / or Data Studio)

Excellent interpersonal skills, communication, problem solving, conflict management, client-focused, customer-driven and able to work under pressure.

Prepare detailed documentation to transfer knowledge and satisfy governance and regulatory concerns.

Mathematics, planning, priority setting, problem resolution, decision making, excellent oral/written communication skills.

Expert knowledge of Data Mining, Databases, SQL, Machine learning.

Experience with the following technologies/databases: Redshift, Oracle, Spark (PySpark), Python, BI Tools (e.g. Tableau)

Strong knowledge of Canadian Payment Industry, payments transaction data and process flows.

·Data Scientist/ Machine Learning Engineer with over 5+ years of experience in handling

·Experience with JBig Data Spark , Scala, Flink.

·Experience to follow up with agile processes.

·Experience with using Jenkins job, CI/CD, kubernetes Awareness of working with Agile work model and implementation.

·Domain experience in Telecom or retail.

·Should have good analytical skills.

- Experience working with Stakeholders on a day to day basis to gather requirements

- Minimum 3 years of experience in Data Analyst

- Experience and understanding of Procurement Data

- Strong Experience with Power Query (Dax and M Language)

- Strong Experience with PowerBI creating dashboards and Power query

- Experience with Data Lake's and gathering data from two or more ERP