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Senior Python Data Analysis Jobs in Massachusetts

The Senior GEOINT Data Scientist will leverage their strong technical background and knowledge to ... HTML 5/Javascript, ArcObjects, Python, Model Builder, Oracle, SQL, GIScience, Geospatial Analysis ...

About the Role We are looking for a sharp, tenacious, and thorough Senior Data Scientist to join ... Proven experience in the use of the main data-science, analytics, modeling and visualization Python ...

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Senior Python Data Analysis information

What is a senior Python data analyst?

A Senior Python Data Analyst is an experienced professional who uses Python programming to collect, process, and analyze large sets of data. They are responsible for extracting meaningful insights from data to support business decisions, often using libraries like pandas, NumPy, and matplotlib. In addition to technical skills, they also apply statistical analysis and data visualization techniques, and frequently mentor junior analysts or collaborate with data scientists and engineers. Their role may also involve developing automated data pipelines and ensuring data quality across projects.

What are the key skills and qualifications needed to thrive as a senior Python data analyst?

To thrive as a Senior Python Data Analyst, you need an in-depth understanding of data analysis, statistical modeling, and advanced Python programming, typically supported by a degree in a quantitative field. Proficiency with data analysis libraries (like pandas, NumPy, and SciPy), visualization tools (such as Matplotlib and Seaborn), and experience with SQL databases are essential, and certifications like Microsoft Certified: Data Analyst Associate can be beneficial. Strong problem-solving abilities, effective communication, and the capacity to distill complex data insights for stakeholders are critical soft skills. These competencies enable you to extract actionable insights from large datasets, drive data-informed decision-making, and collaborate effectively across teams.

What are some common challenges senior Python data analysts face when working with large datasets, and how can they overcome them?

Senior Python Data Analysts often encounter difficulties such as slow processing speeds, memory limitations, and data quality issues when handling large datasets. To overcome these challenges, it's essential to leverage efficient libraries like pandas and Dask, utilize optimized data formats (such as Parquet), and implement batch processing or cloud-based solutions. Collaborating closely with data engineers and IT teams also helps ensure robust data pipelines and infrastructure. Regular code optimization and staying updated on best practices can further enhance performance when working at scale.

What is the difference between Senior Python Data Analysis vs Data Scientist?

AspectSenior Python Data AnalysisData Scientist
Required SkillsPython, SQL, data visualization, statistical analysisPython, R, machine learning, statistical modeling
Work EnvironmentData analysis teams, business unitsResearch, product development, analytics teams
Industry UsageBusiness intelligence, finance, marketingTech, healthcare, finance, research
CertificationsPython certifications, data analysis coursesData science certifications, machine learning courses

While both roles involve Python and data handling, Senior Python Data Analysts focus on interpreting data and creating reports for business decisions, whereas Data Scientists develop predictive models and advanced algorithms to extract deeper insights. The roles often overlap, but Data Scientists typically require broader skills in machine learning and statistical modeling.

What are the most commonly searched types of Python Data Analysis jobs in Massachusetts?

The most popular types of Python Data Analysis jobs in Massachusetts are:

What are popular job titles related to Senior Python Data Analysis jobs in Massachusetts?

For Senior Python Data Analysis jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Senior Python Data Analysis jobs in Massachusetts look for?

The top searched job categories for Senior Python Data Analysis jobs in Massachusetts are:

Senior Manager, Data Analytics and Insights

Boston, MA • On-site

Fidelity Investments
Investment Management and Consulting Services • 10K+ employees

$131K - $166K/yr

Full-time

Posted 29 days ago


Fidelity Investments rating

8.7

Company rating: 8.7 out of 10

Based on 274 frontline employees who took The Breakroom Quiz


Job description

Job Description:

Note: Fidelity will not provide immigration sponsorship for this position.

Position Description:

Analyzes and builds equity datasets and analytical outputs used across quantitative research, risk modeling, and performance attribution. Calculates and applies a broad range of equity analytics, including portfolio risk, return attribution, EPS, fundamental ratings, and fundamental equity factors, across granular and aggregated analytical layers. Maintains complex SQLbased transformations, analytical datasets, and factormodel components that serve as foundational inputs to quantitative research and performance attribution algorithms. Develops diagnostic routines, dataprofiling scripts, and integrity checks to monitor computational accuracy, detect anomalies, and ensure deterministic analytical outputs across distributed systems. Implements and evolves data domains, model enhancements, and analytical capabilities by architecting ingestion frameworks, integrating vendor datasets, and optimizing storage and computer environments for highvolume model execution.

Primary Responsibilities:

  • Performs endtoend reporting and analytics operations, ensuring timely, accurate, and reliable delivery of daily, weekly, monthly, and adhoc analytical outputs across key business areas.

  • Ensures data availability, quality, and process stability, monitoring inputs, workflows, and analytical outputs to maintain high standards of data integrity and reporting accuracy.

  • Responds to complex, adhoc analytical requests, providing data-driven insights and support for strategic initiatives, research projects, and leadership priorities.

  • Develops and enhances analytical tools, dashboards, and visualizations to communicate trends, business drivers, and performance insights to a wide range of stakeholders.

  • Designs, improves, and automates data and analytical processes, including developing new calculations, identifying data anomalies, and creating new reporting capabilities.

  • Participates in multiple concurrent projects, assists with planning, prioritization, resource co-ordination, risk assessment, and timely delivery in a fastpaced environment.

  • Acts as a primary liaison across business partners, technology teams, research groups, and external vendors, ensuring alignment and clear communication throughout the analytics ecosystem.

  • Troubleshoots and resolves data or technology issues, ensuring continuity in analytical pro-duction and delivery of highquality outputs.

  • Provides analytical and technical guidance to senior leadership, contributing to strategic planning materials, prototypes, and recommendations.

  • Mentors and develops junior team members.

Education and Experience:

Bachelor's degree in Finance, Economics, Business Analytics, Computer Science, Engineering, or a closely related field (or foreign education equivalent) and five (5) years of experience as a Senior Manager, Data Analytics and Insights (or closely related occupation) performing portfolio risk, return attribution, and equity and data analytics.

Or, alternatively, Master's degree in Finance, Economics, Business Analytics, Computer Science, Engineering, or a closely related field (or foreign education equivalent) and three (3) years of experience as a Senior Manager, Data Analytics and Insights (or closely related occupation) performing portfolio risk, return attribution, and equity and data analytics.

Skills and Knowledge:

Candidate must also possess:

  • Demonstrated Expertise (DE) performing quantitative investment research and financial data analysis, including constructing and analyzing security- and portfolio-level datasets; and analyzes and structures earnings-per-share estimates, and analyst forecasts, returns, and active weights, using Python, R, and SQL.

  • DE conducting portfolio performance attribution and risk analysis, including Brinson attribution, decomposition of portfolio returns, evaluation of benchmark-relative performance, analysis of factor exposures and sensitivities, and measurement of portfolio-level risk metrics (tracking error and beta), using Python, SQL, FactSet Portfolio Analysis Tool, and Barra Portfolio Manager.

  • DE designing, developing, and implementing advanced analytical tools, data pipelines, and multi-factor models to support stock selections and investment decision making, including data modeling, automation of recurring calculations, validation of inputs and outputs, and building interactive dashboards and visualizations using Python, SQL, Tableau, and Excel.

  • DE sourcing, validating, and integrating market, fundamental, and reference data to support in-vestment and risk analysis, including working with equity and portfolio datasets, reconciling vendor data, and ensuring data quality and consistency using Bloomberg and FactSet platforms.

Salary: $131,225.00 to $166,000.00/year.

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Fidelity's Onsite Working Model
Fidelity is transitioning to a full-time onsite working model through a phased rollout across regions and roles. Currently, some roles and locations require 100% onsite presence, while others require less. Onsite expectations are likely to evolve as the rollout continues. This transition does not apply to fully remote roles.

Certifications:Category:Business Analytics and Insights

Please be advised that Fidelity's business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.


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