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Entry Level Python Data Science Jobs in Toronto, ON

Data Scientist

Markham, ON

CA$80K - CA$120K/yr

MSc in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field (PhD ... Python, with a solid understanding of software engineering best practices (modularity, code ...

You'llbuild and deliver data science solutions end-to-end, framing problems with partners ... Strong Python skills and Git-based development practices (e.g., version control, peer review ...

Data Science, Statistics, Economics, Mathematics, etc.) with the expectation of graduating in winter 2026 or spring/summer 2027 * Experience with a scientific computing language (such as Python, R ...

You'llbuild and deliver data science solutions end-to-end, framing problems with partners ... Strong Python skills and Git-based development practices (e.g., version control, peer review ...

Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted ... Tune complex SQL queries and Python-based processing jobs to handle petabyte-scale environments ...

Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted ... Tune complex SQL queries and Python-based processing jobs to handle petabyte-scale environments ...

Data Scientist II

Toronto, ON · On-site

CA$81K - CA$115K/yr

Advanced proficiency in SQL, Python for data analysis, automation, and reporting * 2+ years of ... In-depth knowledge of data science tools such as NumPy, pandas, matplotlib or R equivalent

Collaborate with Analytics, Data Science, and Enablement partners to gather requirements and translate business needs into data engineering solutions using Python and SQL * Design, build, and ...

Data Science and Strategic Support * Assist the Data Science Manager in achieving objectives ... Advanced Excel, Power Query, DAX, and Python for analytics. * Microsoft Fabric, Power Platforms ...

Data Engineer

Mississauga, ON · Hybrid

CA$110K - CA$125K/yr

Collaborate with data analysts, data scientists, and business stakeholders to gather data ... Proficiency in Python scripting and Pyspark for data processing and automation. * Experience with ...

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Entry Level Python Data Science information

What are some common challenges faced by entry-level Python data scientists when starting out, and how can they be addressed?

Entry-level Python data scientists often encounter challenges such as managing large datasets, understanding the nuances of real-world data (like missing or inconsistent values), and effectively communicating technical findings to non-technical stakeholders. To address these challenges, it's helpful to develop strong data cleaning skills, practice using libraries like pandas and scikit-learn, and focus on improving data visualization and storytelling abilities. Additionally, seeking feedback from more experienced team members and participating in collaborative projects can accelerate learning and help overcome early hurdles.

What is an entry level Python data scientist?

An entry level Python data scientist is a professional who uses Python programming language to analyze, interpret, and visualize data, typically in the early stages of their data science career. They are responsible for collecting, cleaning, and preparing data, performing basic statistical analyses, and building simple machine learning models under supervision. These roles often require proficiency in Python libraries like pandas, NumPy, and scikit-learn, as well as good problem-solving skills. Entry level data scientists may work in industries such as finance, healthcare, marketing, or technology to help organizations make data-driven decisions.

What are the key skills and qualifications needed to thrive as an Entry Level Python Data Scientist, and why are they important?

To thrive as an Entry Level Python Data Scientist, you need a strong understanding of statistics, data analysis, and proficiency in Python programming, typically supported by a relevant degree or coursework. Familiarity with data science libraries (such as pandas, NumPy, and scikit-learn), data visualization tools, and basic SQL is commonly required. Analytical thinking, problem-solving, and effective communication help you interpret data and present findings clearly. These skills ensure you can extract meaningful insights from data, collaborate effectively, and contribute to data-driven decision-making.

What is the difference between Entry Level Python Data Science vs Entry Level Data Analyst?

AspectEntry Level Python Data ScienceEntry Level Data Analyst
Required SkillsPython, SQL, statistics, machine learning basicsExcel, SQL, data visualization, basic statistics
CertificationsPython programming, data science fundamentalsExcel certifications, basic data analysis courses
Work EnvironmentTech companies, startups, data-driven teamsBusiness departments, marketing, finance teams
Common UsageBuilding models, data cleaning, predictive analyticsReporting, data visualization, trend analysis

Entry Level Python Data Science roles focus on programming, machine learning, and predictive modeling, often requiring Python and statistical knowledge. Entry Level Data Analyst positions emphasize data reporting, visualization, and basic analysis using tools like Excel and SQL. Both roles are common in various industries, but Python Data Science roles typically involve more technical and coding skills, while Data Analyst roles focus on interpreting data for business insights.

What are the most commonly searched types of Python Data Science jobs in Toronto, ON? The most popular types of Python Data Science jobs in Toronto, ON are:
What job categories do people searching Entry Level Python Data Science jobs in Toronto, ON look for? The top searched job categories for Entry Level Python Data Science jobs in Toronto, ON are:
Infographic showing various Entry Level Python Data Science job openings in Toronto, ON as of June 2026, with employment types broken down into 88% Full Time, 4% Part Time, and 8% Contract. Highlights an 93% Physical, 4% Hybrid, and 3% Remote job distribution.

CA$80K - CA$120K/yr

Other

Medical, Retirement

Posted 7 days ago


Job description

Experience Aviva

Together, we are Aviva. Our values - Care, Commitment, Community, and Confidence - guide how we show up for each other and for our customers. Individually, they're words. Together, they define who we are.

At Aviva Canada, we put people first, our employees, our customers, and our communities. We're proud of a culture built on care, inclusion, and collaboration, where your voice matters and your growth is supported. We're not just about insurance; we're about making a real difference by protecting what matters most.

The Opportunity

Join an exciting team of data scientists and engineers at the forefront of using data to drive decisions at every level of our organization. The insurance industry is undergoing a transformation and you get to be in the driver's seat of this data-driven, technology revolution.

As a Data Scientist on the Fraud Data Science team, you'll work closely with a wide range of business partners and help shape future products and solutions. You'll contribute to highimpact initiatives focused on fraud detection, using machinelearningbased solutions to protect customers and the business.

You'll be involved across the full development lifecycle, from idea generation and experimentation through deployment, monitoring, and ongoing support. Your work will include building and deploying data pipelines, machine learning, and statistical models used in realworld applications at scale. The team's models are already running in production, and you'll help expand and evolve these capabilities as part of our ongoing InsurTech transformation.

What you'll do:
  • Design, develop, test, and deploy scalable, productionready code and machine learning models.

  • Transform large, complex datasets into actionable insights, recommendations, and datadriven decisions.

  • Develop innovative approaches to pattern recognition using machine learning, statistical, and analytical techniques.

  • Design and deploy models to realtime APIs, ensuring reliability, performance, and scalability.

  • Communicate insights and model outcomes clearly to both technical and nontechnical audiences.

  • Maintain, enhance, and optimize existing codebases and data pipelines.

  • Drive delivery accountability for both projectbased initiatives and BAU work, aligned to agreed timelines and priorities.

  • Ensure solutions conform to IT and Enterprise Architecture standards where applicable.

What you'll bring:
  • MSc in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field (PhD preferred).

  • 2+ years of experience across the endtoend model development lifecycle, working with large and complex datasets (industry or academic/postdoctoral experience considered).

  • 2+ years of experience programming in Python, with a solid understanding of software engineering best practices (modularity, code reusability, version control, repositories).

  • Proficiency in SQL and Git, with handson experience collaborating in shared codebases.

  • Experience productionizing machine learning models, including monitoring, maintenance, and MLOps practices.

  • Familiarity with data warehouse concepts, ETL strategies and data engineering best practices.

  • A strong track record of building robust, maintainable, highquality code.

  • Ability to operate optimally in a datadriven software engineering environment and translate data into business value.

  • Strong communication and collaboration skills, with the ability to work across disciplines.

What makes you stand out:
  • Experience working with cloudbased data platforms and technologies such as PostgreSQL, Teradata, Hadoop, and AWS.

  • Experience with CI/CD pipelines and modern deployment practices.

  • Exposure to fraud, insurance, or highly regulated domains.

  • Handson experience building and consuming APIs.

  • A creative, curious, and resourceful approach to problem solving .

What you'll get:
  • The salary band for this position ranges from $80,000 to $120,000. Please note that individual salary is determined by factors such as job-related knowledge, skills and experience, as well as internal equity.

  • Compelling rewards package including base compensation, eligibility for annual bonus, retirement savings, share plan, health benefits, personal wellness, and volunteer opportunities.

  • Hybrid flexible work model.

  • Outstanding career development opportunities.

  • We'll support your professional development education.

  • Competitive vacation package with the option to purchase 5 extra days off per year.

  • Employee-driven programs focused on gender, LGBTQ+, origins, diversity, and inclusion.

  • Corporate wellness programs to support our employees' physical and mental health.

This job advertisement is for an existing vacancy which has been posted both internally & externally.

Aviva Canada may use AI (Artificial Intelligence) tools to assist us throughout the recruitment process to screen, assess or select applicants for a position.

Aviva Canada welcomes applications from all qualified individuals and has a process in place to provide accommodations for persons with disabilities at all stages of the hiring process and during employment. If you require an accommodation during the interview or hiring process, please contact your Aviva Talent Acquisition Partner so that an appropriate accommodation can be arranged.

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