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Python Analytics Jobs in Massachusetts (NOW HIRING)

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Java with Python Developer

Boston, MA · On-site

$78K - $120K/yr

... analyse results, and coordinate bug fixes to uphold the software quality standards • Develop ... Python PySpark Java Springboot, Microservices, API/Rest Services, AWS Services, Redshift Postgres ...

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Python Analytics information

What are the key skills and qualifications needed to thrive as a Python Analytics professional?

To thrive as a Python Analytics professional, you need a strong background in statistics, data analysis, and proficiency in Python programming, often supported by a degree in computer science, mathematics, or a related field. Familiarity with data analytics libraries (such as pandas, NumPy, and scikit-learn), data visualization tools, and experience with databases are typically required. Strong problem-solving, communication, and critical thinking skills help in interpreting data and conveying insights to stakeholders. These abilities are crucial for turning complex data into actionable business decisions and driving organizational success.

Which Python Analytics job is in demand?

Python Analytics roles such as Data Analyst, Data Scientist, and Business Intelligence Analyst are currently in high demand across various industries. These positions typically require proficiency in Python, data visualization, and statistical analysis, with skills in tools like Pandas, NumPy, and machine learning frameworks increasing employability.

What is the difference between Python Analytics vs Data Analyst?

AspectPython AnalyticsData Analyst
Required SkillsPython programming, data manipulation, statistical analysisExcel, SQL, basic statistics
CertificationsPython certifications, data analysis coursesNone typically required, but certifications like CAP or Microsoft certifications are common
Work EnvironmentData science teams, analytics departments, tech companiesBusiness units, marketing, finance, consulting firms
ToolsPython libraries (Pandas, NumPy, scikit-learn)Excel, SQL, Tableau, Power BI

Python Analytics involves using Python programming to perform advanced data analysis, modeling, and automation, often requiring coding skills. Data Analysts focus on interpreting data using tools like Excel and SQL, providing reports and insights. While both roles analyze data, Python Analytics typically involves more technical and programming expertise, making it suitable for complex data projects and predictive modeling.

What are some typical challenges faced by professionals in Python Analytics roles, and how can I prepare for them?

Professionals in Python Analytics roles often encounter challenges such as handling large and complex datasets, ensuring data quality, and communicating insights effectively to non-technical stakeholders. To prepare, it's beneficial to strengthen your skills in data cleaning, visualization libraries (like Matplotlib or Seaborn), and learn best practices for writing efficient, reproducible code. Collaborating closely with data engineers, business analysts, and decision-makers is also a key part of the job, so developing strong communication and teamwork abilities will help you succeed.

What is a Python Analytics professional?

A Python Analytics professional is someone who uses the Python programming language to collect, process, analyze, and interpret data in order to help organizations make data-driven decisions. They often work with large datasets, perform statistical analyses, create data visualizations, and build predictive models. These professionals may work in industries such as finance, healthcare, marketing, or technology, and typically use libraries like Pandas, NumPy, and Matplotlib. Their work helps businesses gain insights, optimize processes, and solve complex problems through data.

Is Python good for data analytics?

Python is widely used in data analytics roles due to its extensive libraries such as Pandas, NumPy, and Matplotlib, which facilitate data manipulation, analysis, and visualization. Its simplicity and versatility make it a preferred language for data analysts and data scientists, often complemented by skills in SQL and data modeling. Proficiency in Python can enhance job prospects in data analytics positions.
What are popular job titles related to Python Analytics jobs in Massachusetts? For Python Analytics jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Python Analytics jobs in Massachusetts look for? The top searched job categories for Python Analytics jobs in Massachusetts are:
What cities in Massachusetts are hiring for Python Analytics jobs? Cities in Massachusetts with the most Python Analytics job openings:
Python Analytics jobs near you
Infographic showing various Python Analytics job openings in Massachusetts as of July 2026, with employment types broken down into 1% Internship, 86% Full Time, 10% Part Time, 1% Temporary, and 2% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution.

Director, Portfolio Analytics

Fidelity Investments

Boston, MA • On-site

Full-time

Posted 22 days ago

Fidelity Investments rating

8.7

Company rating: 8.7 out of 10

Based on 271 frontline employees who took The Breakroom Quiz

15th of 150 rated financial services

Job description


Position Description:
Note: Fidelity will not provide immigration sponsorship for this position.
Oversees production data management, model integrity, and end-to-end technical support for portfolio management, risk models, and quantitative research platforms, by building quantitative research platforms and tools. Ensures complete data quality coverage, Service Level Agreement (SLA) documentation, and proper team communication. Drives the buildout of new data quality frameworks and tools to streamline teamwork in support of Data Quality (DQ) coverage at scale. Draws on in-depth knowledge of advanced principles, theories, and concepts to create high quality quantitative research solutions for complex projects, applications, and products. Consults with development architects and business on internal service quality control standards, policies, and procedures.
Primary Responsibilities:
  • Develops new processes, performs calculations, identifies anomalies, and produces new reporting capabilities by analyzing large data sets.
  • Evaluates the value of new content and methods through proofs-of-concept.
  • Extends data platforms using existing data models and quantitative research processes.
  • Translates analytics into model construction, factor definition, and calculation.
  • Develops and incorporates non-traditional and unstructured data and data science applications to enhance research and investment process.
  • Performs validations and testing of models to ensure adequacy and reformulate models as necessary.
  • Presents mathematical modeling and data analysis results to management and other end users.
  • Formulates and applies mathematical modeling and other optimizing methods to develop and interpret information that assists with decision making.
  • Collects and analyzes data and develops decision support software, service, or products.
  • Develops and supplies optimal time, cost, or logistics networks for program evaluation, review, or implementation.
  • Advises senior management on technical strategy.
  • Participates in high-level, cross-functional design teams.
  • Sets vision, goals, and direction of team/organization.
  • Plans and leads organization-wide initiatives.
  • Provides leadership, technical supervision, and expertise to multiple teams in broad technical areas on complex organization-wide projects.
  • Researches and recommends new technologies.
  • Regularly provides guidance, training, and coaching to other team members for performance and career development.
  • Identifies and plans for future resource needs.

Education and Experience:
Bachelor's degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and six (6) years of experience as a Director, Portfolio Analytics (or closely related occupation) performing multi-asset class analytics in a financial services environment.
Or, alternatively, Master's degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and four (4) years of experience as a Director, Portfolio Analytics (or closely related occupation) performing multi-asset class analytics in a financial services environment.
Skills and Knowledge:
Candidate must also possess:
  • Demonstrated Expertise ("DE") performing product management and impact analysis on trading and risk analytics in a complex multi-asset class environment (open and closed architecture fund-of-funds structures); debugging differences between economic and accounting views of holdings and assessing their influence on portfolio construction; monitoring and measuring risk for mutual funds; and writing specification documents, interpreting business requirements, and creating analytical visualization solutions, using Microsoft Office suite, Visual Basic (VBA), Tableau and Oracle SQL.
  • DE defining and maintaining operational workflows; creating data quality assurance tools for validating holdings from various vendors (Morningstar, Bloomberg, Index providers and accounting views) and instrument data across multi-asset classes (Equity, Corporate Bonds, Municipal Bonds, Commodities, Derivatives, and Alternative strategies), using Oracle SQL, Snowflake, Python, Microsoft Excel, and Visual Basic (VBA); and cleaning, validating, cross-checking, tracking, and documenting changes, anomalies, and inconsistencies in raw data for investment risk analysis.
  • DE analyzing BarraOne Multi-Asset Class (MAC) risk factor model construction, factor definitions, and calculations; translating equity, fixed income, alternatives risk and stress analytics into meaningful insights used for portfolio maintenance; integrating BarraOne risk models into existing infrastructure, and expanding and enhancing analytic platforms and tools, using Microsoft Excel, Snowflake, Tableau, Oracle SQL, Python, and R; and performing investment risk analysis (portfolio performance and risk reporting), using BarraOne Multi-Factor Model (MAC) risk and performance attribution.
  • DE measuring incremental effects of portfolio construction methodologies; performing fund holdings and returns analysis, using statistical methods and analytical tools - Analysis of Variance (ANOVA) and Analysis of Covariance (ANCOVA); writing risk model methodologies and specification documents, interpreting business requirements, and creating model performance monitoring reports in Confluence and Microsoft Office Suite; integrating portfolio management workflows into vendor tools (Factset and MSCI BarraOne), using Microsoft Office Suite, Tableau, Oracle SQL, Snowflake, Python, and R; and researching and testing methods to improve existing models, using regression techniques, time series analysis, and interest rate models and Monte Carlo simulations.

Salary: $165,000.00 to $194,000.00/Year.
#PE1M2
#LI-DNI
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:
Data 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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