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Weekend Python Data Analyst Jobs in Calgary, AB (NOW HIRING)

Apply risk management systems and analytical tools (ETRM, Excel, Python, R) to build, validate, and maintain pricing models and data workflows. Query and integrate market data using SQL and data APIs ...

Write clean, efficient, and maintainable SQL and Python code to transform raw data into curated, analysis-ready datasets. * Build reliable transformation workflows that support analytics, reporting ...

Proficiency in Python or similar languages for data processing and analytics. * Experience leveraging AI capabilities and tools (such as Vertex AI) to build machine learning models and AI solutions ...

... data analysis and modeling using Python. • Experience with databases and programming languages (SQL, Oracle, Hadoop, NoSQL) for data manipulation and integration. • Experience with cloud ML ...

Data Theorem is an exciting company focused on creating a more secure world for data. Rooted in a ... Some experience writing tools in Python. * Bonus points: experience with taking apart iOS software ...

Data is deeply embedded in the product, engineering, analytics, and operational culture at Finning ... cause analysis, escalation, and knowledge management. * Working knowledge of Python, PySpark ...

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Weekend Python Data Analyst information

What are some common challenges faced by Weekend Python Data Analysts, and how can they be managed?

Weekend Python Data Analysts often face challenges such as limited time to access stakeholders or full datasets, since many team members may not be available outside standard business hours. To manage these challenges, it’s important to communicate needs and data access requirements ahead of time, and to document findings thoroughly for seamless handovers. Being self-sufficient with Python tools and data wrangling is critical, as you may need to troubleshoot issues independently. Proactively setting clear goals for each shift can also help maximize productivity during weekend hours.

What is a Weekend Python Data Analyst?

Weekend Python Data Analysts are professionals who work part-time or on weekends to analyze data using Python programming. They typically handle tasks such as cleaning data, performing statistical analyses, creating data visualizations, and generating reports. These analysts often support organizations that require flexible staffing or have projects that need attention outside of regular business hours. Their expertise in Python enables them to efficiently manipulate large datasets and extract actionable insights. This role is ideal for those seeking flexible work arrangements or supplementary income in the data analytics field.

What are the key skills and qualifications needed to thrive as a Weekend Python Data Analyst?

To thrive as a Weekend Python Data Analyst, you need strong analytical skills, proficiency in Python programming, and a background in statistics or data science—often supported by a relevant degree or certification. Familiarity with data visualization tools (like Tableau or Power BI), SQL databases, and Python libraries such as Pandas and NumPy is typically expected. Excellent problem-solving, time management, and communication skills help you interpret data insights and present findings effectively during limited weekend hours. These skills ensure accurate data analysis, actionable recommendations, and efficient collaboration, even within a compressed work timeframe.

What is the difference between Weekend Python Data Analyst vs Weekend Data Scientist?

AspectWeekend Python Data AnalystWeekend Data Scientist
Required SkillsPython, data analysis, visualization, SQLPython, machine learning, statistical modeling, data analysis
CertificationsData analysis certifications, Python certificationsData science certifications, Python certifications
Work EnvironmentPart-time, project-based, remote or on-sitePart-time, project-based, remote or on-site
Industry UsageBusiness analytics, finance, marketingResearch, AI development, advanced analytics

Weekend Python Data Analysts focus on data cleaning, visualization, and basic analysis using Python, suitable for business insights. Weekend Data Scientists handle more complex modeling and machine learning tasks, often requiring advanced statistical skills. Both roles are part-time, flexible, and commonly used across industries, but Data Scientists typically require a deeper technical background.

What are the most commonly searched types of Python Data Analyst jobs in Calgary, AB? The most popular types of Python Data Analyst jobs in Calgary, AB are:

Sr. Analyst, Market Data

Capital Power

Calgary, AB • On-site

Full-time

Retirement, PTO

Re-posted 25 days ago


Job description

A little about Capital Power

Capital Power (TSX: CPX) is dedicated toPowering Change by Changing Power. This north star guides our ambitions, focus, and actions as we transform our energy system. We're a growth-oriented North American energy company headquartered in Edmonton, Alberta. Our team safely delivers, builds, and creates balanced energy solutions for customers across North America.

Our people are at the core of our journey to deliver reliable, affordable, and lower-carbon power solutions. We provide purpose-driven work in a safe and inclusive environment, and we live by our North Star. With us, your contributions matter - we want you to be empowered to innovate, collaborate, and ultimately drive results. We're here to partner with you so you can learn, grow, and forge a career that's meaningful to you. Join us in powering North America!


Your Opportunity:

OnePermanentFull TimePosition.


TheSr. Analyst, Market Dataowns Capital Power's end-to-end price curve framework within the Risk Group. The role is accountable for the quality, integrity, and governance of all priceand market datacurves used across the commodity portfolio, spanning new curve intake,methodologydesign, system configuration, daily productionand validation, independent price verification (IPV), and governance reporting.

The successful candidate will combine strong quantitative and systems skills with sound professional judgment and a commitment to robustcontrols andwill serve as the subject-matter expert on all matters related to commodityand market datacurves.


You will contribute to our team by:


Key Accountabilities:

Serve as the single point of contact for all newcommodity and market datacurve requestsandmanage the intake process from request through governance approval.

Design, build, calibrate, and document forward price curve models across commodities and delivery points, including directly observable, interpolated, and proxy / spread-to-benchmark approaches.

Own andmaintainthe central curve register, ensuring all curves are catalogued with current attributes, approval status, and scheduled review dates.

Configure andmaintainapproved price curves in ZEMA (data ingestion, quality rules, curve construction logic) and Allegro (curve definition, valuation formulas, P&L attribution); lead UAT and production deployment.

Monitor daily curve production across all curves; investigate and resolve data feed failures, quality alerts, andotherflags within EOD SLAs;maintainand test fallback procedures.

Execute the firm's dailyvalidationandmonthlyindependent price verification (IPV) process; comparecurveoutputs to independent market sources; prepare and distribute IPV reports; escalate material exceptions.

Conduct or coordinate independent validation of all new and materially modified price curve models; issue structured validation reports; track findings to remediation; manage the periodic revalidation schedule.

Prepare and present submissions toRisk OversightCommittee; produce periodic governance reports covering inventory status, open findings, IPV exception trends, and curve performance.

Maintain the model risk and governance framework for price curves in alignment with Model Risk Policy and applicable regulatory guidance; support audits and regulatory examinations.


What you will bring to the role:


Education & Experience:

Post-secondary degree in Finance, Economics, Mathematics, Engineering, or a related field.

Advanced degree (e.g., Master's, PhD) or professional designation (e.g., CFA, FRM, PRM) is an asset.

5-7+ years inriskmanagement, market data, model validation, or quantitative risk in a commodity trading or energy environment.

Hands-on experience building orvalidatingforward price curves, including proxy / spread-to-benchmark methodologies with regression-based parameter calibration.

Direct experience with ZEMA and / or Allegro in a production environment strongly preferred.

Familiarity with model risk frameworks andorganizedcommodity markets (AESO, IESO,CAISO, MISO,ERCOT, PJM, Henry Hub,environmental) preferred.


Technical Skills:

Apply risk management systems and analytical tools (ETRM, Excel, Python, R) to build, validate, and maintain pricing models and data workflows.

Query and integrate market data using SQL and data APIs (e.g., ICE Data Services, ZEMA, Nodal) to support curve production and validation processes.

Automate repetitive data processes and controls using scripting, with an ability to identify opportunities to streamline manual workflows.

Develop, validate, and maintain pricing methodologies, including proxy/spread-to-benchmark and regression-based approaches, across liquid and illiquid markets.

Demonstrate working knowledge of power market data, forward price curves, and valuation models in regional markets (e.g., WECC, AESO, PJM).

Leverage AI and emerging analytical tools (e.g., Copilot, LLMs, machine learning libraries) to enhance data quality checks, anomaly detection, and reporting efficiency, or demonstrate a genuine curiosity and willingness to explore these tools as they evolve.

Communicate technical content clearly in writing and verbally; able to present pricing governance updates, exception analysis, and model validation findings to committees and senior stakeholders.


Working Conditions:

  • Hybrid office/workfromhome environment.
  • Minimal travel required
  • Candidates must be legally eligible to work in Canada
  • The successful candidate will undergo education verification, reference checks, and a criminal and credit record check

Additional Details:

Capital Power employeesthatrefera successful candidate for this positionare eligible for a$1000Referral Reward!


We believe that supporting employee physical, mental, financial, and social well-being is critical to our success. We offer a comprehensive package including flexible benefits, retirement savings programs, paid time off, and ongoing development opportunities.


This role includes a competitive base salary, annual incentive, and participation in Capital Power's long-term incentive program.


How To Apply and Next Steps

Capital Power only accepts resumes via online application atwww.capitalpower.com/careers. If you choose to submit your resume by any other means, we cannot guarantee that your application will be considered for vacancies.
Applicants with disabilities who require a reasonable accommodation to complete their application can request accessible formats, communication support, or other accessibility assistance by contactingcareers@capitalpower.com.
Capital Power is committed to providing a fair and transparent hiring process. We recognize and embrace the value of diversity and hire employees with the appropriate skills, experience and knowledge for each position.
Thank you for taking the time to apply and expressing interest in powering a sustainable future with Capital Power! We wish that we could personally respond to everyone who applies; however, it is our practice to contact only those individuals selected for interviews.