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Data Science And Analytics Jobs in Philadelphia, PA

Data Scientist

Conshohocken, PA · On-site +1

$175K/yr

Data Science & Advanced Analytics * Analyze large and complex datasets to identify patterns, trends, and opportunities that support strategic business decisions. * Develop predictive models, scoring ...

At least five years of experience in data science, analytics, data engineering or digital transformation roles. * Strong expertise in data architecture, data modeling and modern data science ...

Data Science Tutor

Trenton, NJ · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Data Science Tutor

Chester, PA · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Oversees and engages in deep dive diagnostic, predictive, and prescriptive analytics to support ... Manages a team of data scientists responsible for a portfolio of diagnostic, predictive, and ...

Manager Data Science

Philadelphia, PA · On-site

$115K - $192K/yr

At Elsevier, data science leadership is about far more than managing projects, models, or roadmaps ... Partner closely with Product, Engineering, Research, UX, Analytics, and domain experts to shape ...

At Elsevier, data science leadership is about far more than managing projects, models, or roadmaps ... Partner closely with Product, Engineering, Research, UX, Analytics, and domain experts to shape ...

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Showing results 1-20

Data Science And Analytics information

See Philadelphia, PA salary details

$37.8K

$123.9K

$198.3K

How much do data science and analytics jobs pay per year?

As of Aug 23, 2026, the average yearly pay for data science and analytics in Philadelphia, PA is $123,854.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,400.00 and $137,200.00 per year, depending on experience, location, and employer.

What is data science and analytics?

Data Science and Analytics refer to the fields that focus on extracting meaningful insights from large and complex data sets. Data Science combines statistics, computer science, and domain knowledge to analyze data, build predictive models, and support data-driven decision-making. Analytics, which is a core part of data science, involves examining data to discover trends, patterns, and correlations that can help organizations solve problems or improve processes. Professionals in these fields use tools such as Python, R, SQL, and machine learning algorithms to analyze data and communicate findings to stakeholders.

What are some common challenges faced by data science and analytics professionals when working with cross-functional teams?

Data science and analytics professionals often collaborate with colleagues from diverse backgrounds such as engineering, marketing, and business operations. One common challenge is translating complex analytical findings into actionable insights that non-technical stakeholders can easily understand. Additionally, aligning project objectives and timelines across teams can require strong communication and project management skills. Overcoming these challenges is essential for ensuring that data-driven solutions are effectively implemented and contribute to organizational goals.

What are the key skills and qualifications needed to thrive as a data science and analytics professional, and why are they important?

To thrive in Data Science and Analytics, you need strong skills in statistics, data manipulation, and programming, typically backed by a degree in computer science, mathematics, or a related field. Proficiency with tools like Python, R, SQL, and data visualization platforms such as Tableau, along with knowledge of machine learning frameworks, is highly valued. Strong problem-solving ability, critical thinking, and effective communication skills help translate complex data findings into actionable business insights. These skills are crucial for turning raw data into strategic decisions that drive organizational success.

What is the difference between Data Science And Analytics vs Data Analysis?

AspectData Science And AnalyticsData Analysis
Required SkillsStatistical modeling, programming, machine learningData cleaning, descriptive statistics, visualization
Work EnvironmentCross-functional teams, R&D, predictive modelingBusiness reporting, dashboards, ad hoc analysis
Tools & TechnologiesPython, R, SQL, Hadoop, SparkExcel, SQL, Tableau, Power BI
Industry UsageTech, finance, healthcare, marketingRetail, finance, healthcare, operations

Data Science And Analytics involves advanced techniques like machine learning and predictive modeling, often requiring programming skills. Data Analysis focuses on interpreting existing data through descriptive statistics and visualization for decision-making. Both roles are essential but differ in complexity and scope.

What can I do with data science and analytics?

Data science and analytics professionals analyze large datasets to extract insights, support decision-making, and improve business processes. They use tools like Python, R, and SQL, and often work in environments that require strong statistical and programming skills. These roles can lead to careers in industries such as finance, healthcare, marketing, and technology, with opportunities for advancement and specialization.

What jobs can I get with a data science and analytics degree?

A degree in data science and analytics can lead to roles such as data analyst, data scientist, business intelligence analyst, machine learning engineer, and data engineer. These positions typically require skills in programming languages like Python or R, data visualization tools, and statistical analysis, often with certifications or experience in big data platforms and SQL. Job responsibilities include interpreting complex data, building predictive models, and supporting data-driven decision-making.

What cities near Philadelphia, PA are hiring for Data Science And Analytics jobs?

Cities near Philadelphia, PA with the most Data Science And Analytics job openings:

Infographic showing various Data Science And Analytics job openings in Philadelphia, PA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $123,854 per year, or $59.5 per hour.

Data Scientist

Soni Resources

Conshohocken, PA • On-site, Remote

$175K/yr

Full-time

Re-posted 13 days ago


Job description

Data Scientist (Data Science + Data Engineering)
Location: Remote (Preference for Northeast/Mid-Atlantic; monthly travel to Plymouth Meeting, PA as needed)
Our client is building a data-driven culture where analytics, AI, and technology directly influence business decisions. They are seeking a Data Scientist who can translate complex business challenges into actionable insights while helping bring advanced analytics and machine learning solutions into production.
This role is ideal for someone who enjoys the full lifecycle of data science-from exploring data and building predictive models to partnering with engineering teams to deploy solutions that create measurable business value. The successful candidate will work closely with data engineers, business stakeholders, and executive leadership to help shape the future of analytics and AI across the organization.
While this is primarily a Data Science role, candidates should have a solid understanding of data engineering concepts and how models are operationalized within modern data ecosystems.
Responsibilities:
Data Science & Advanced Analytics
  • Analyze large and complex datasets to identify patterns, trends, and opportunities that support strategic business decisions.
  • Develop predictive models, scoring frameworks, and machine learning solutions that enhance business performance and decision-making.
  • Apply statistical and analytical techniques to solve real-world business problems and uncover actionable insights.
  • Continuously evaluate model effectiveness and recommend enhancements based on business outcomes and evolving data.
AI & Innovation
  • Contribute to the organization's growing AI strategy, including opportunities to leverage generative AI and emerging technologies.
  • Explore innovative approaches to automation, decision support, and workflow optimization through advanced analytics and AI solutions.
  • Partner with leadership to identify high-value use cases where AI can improve operational efficiency and decision quality.
Data Engineering Collaboration
  • Work closely with data engineering teams to ensure analytical solutions can be deployed, maintained, and scaled effectively.
  • Collaborate on the design and implementation of data pipelines that support machine learning and advanced analytics initiatives.
  • Help bridge the gap between model development and production deployment by ensuring solutions are practical, reliable, and business-ready.
  • Support efforts to improve data quality, accessibility, and governance across the organization.
Business Partnership
  • Engage directly with business stakeholders to understand challenges, define analytical approaches, and deliver impactful solutions.
  • Translate technical findings into clear, concise recommendations for both technical and non-technical audiences.
  • Serve as a trusted partner in helping business leaders make data-informed decisions.
Qualifications
Required
  • 3+ years of hands-on experience in Data Science, Analytics, Machine Learning, or a related quantitative field.
  • Proven experience developing predictive models or machine learning solutions in a business environment.
  • Strong proficiency in Python and modern data science libraries.
  • Advanced SQL skills and experience working with large-scale, complex datasets.
  • Experience applying statistical analysis and predictive modeling techniques to business problems.
  • Understanding of data engineering concepts, including data pipelines, model deployment, and production environments.
  • Experience working with cloud-based platforms such as Azure, AWS, or Google Cloud.
  • Strong communication and stakeholder management skills with the ability to explain technical concepts to business audiences.
Preferred
  • Experience collaborating closely with Data Engineering teams or supporting machine learning deployment initiatives.
  • Familiarity with distributed computing tools such as Spark or PySpark.
  • Experience developing AI-driven solutions, including Generative AI, Large Language Models (LLMs), or agent-based workflows.
  • Background in insurance, financial services, or other highly regulated industries.
  • Experience building production-grade machine learning applications.
  • Master's or PhD in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related quantitative discipline.

The ideal candidate:
  • Enjoys solving complex business problems through data.
  • Approaches challenges with curiosity and asks thoughtful questions.
  • Can balance analytical rigor with practical business impact.
  • Is comfortable working independently while collaborating across teams.
  • Takes ownership and drives projects from concept through implementation.
  • Learns new technologies and business domains quickly.
  • Values building solutions that can be used and adopted by the business-not just creating models.

Soni Resources logo

About Soni Resources

Sourced by ZipRecruiter

Soni is a premier staffing & recruitment company that is disrupting the human capital management space. Headquartered in New York, Soni has presence in 23 markets across the United States. We support each professional relationship with a cutting-edge approach, industry-leading insights, and a human touch. We are trusted to help companies and individuals tackle their challenges and capture their greatest opportunities. We are minority-owned, and diversity & inclusion is in our DNA. We are committed to creating environments where people are empowered to be their authentic selves.

Company size

11 - 50 Employees

Headquarters location

New York, NY, US