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Data Analytics Computer Science Jobs in Pennsylvania

MSD

Assoc. Dir , Data Analysis

North Wales, PA · On-site

Active Listening, Business, Business Intelligence (BI), Commercial Analytics, Computer Science, Data Analysis, Data Management, Data Modeling, Data Visualization, Digital Marketing, Inclusive ...

GIRARD ESTATE

Computer Science Teacher

Philadelphia, PA

$50K - $70K/yr

Use assessment data to inform instructional decisions * Provide timely, meaningful feedback to ... Grades 7-12 Computer Science * Strong content knowledge in computing and digital systems

Cmu

Data Scientist

Pittsburgh, PA

Requirements: * BS in data science, machine learning, computer science, statistics, or related ... Innovative and inquisitive with ability to imagine novel analytical solutions to problems Thrives ...

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All JobsData Analytics Computer Science JobsData Analytics Computer Science Jobs in Pennsylvania

Data Analytics Computer Science information

Is 40 too late for data science?

Data analytics and data science roles are open to individuals of all ages, and many professionals transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and tools like Python or R, regardless of age. Continuous learning and practical experience are key factors for career advancement in this field.

What is the difference between Data Analytics Computer Science vs Data Science?

AspectData Analytics Computer ScienceData Science
Required CredentialsBachelor's in Computer Science, Data Analytics, or related fields; certifications like Google Data AnalyticsBachelor's or higher in Computer Science, Statistics, or related; certifications like Certified Data Scientist
Work EnvironmentBusiness settings, analytics teams, IT departmentsResearch labs, tech companies, consulting firms
Employer & Industry UsageFinance, healthcare, marketing, retailTech, finance, healthcare, academia

Data Analytics Computer Science focuses on analyzing data to inform business decisions using programming and statistical tools. Data Science encompasses a broader scope, including developing models, machine learning, and predictive analytics. While both roles require similar credentials and often work in overlapping industries, Data Science typically involves more advanced statistical and modeling skills, whereas Data Analytics Computer Science emphasizes data processing and visualization for decision-making.

What is the salary of a 2 year experience data scientist?

A data scientist with two years of experience typically earns between $70,000 and $100,000 annually, depending on the industry, location, and skill set. Proficiency in programming languages like Python or R, along with experience in machine learning and data visualization tools, can influence salary levels.

Is AI replacing data analysts?

Data analysts play a crucial role in interpreting data and providing insights, and AI tools are designed to assist rather than replace them. AI can automate routine tasks and enhance data processing, but human expertise is still essential for complex analysis, decision-making, and contextual understanding. Developing skills in data visualization, programming, and machine learning can help data analysts stay valuable in an evolving job market.

Can computer science work as a data analyst?

A computer science degree provides a strong foundation in programming, algorithms, and data management, which are essential skills for a data analyst. Data analysts typically use tools like SQL, Excel, and statistical software, and may benefit from knowledge of programming languages such as Python or R. While a computer science background is valuable, additional training in data visualization and statistical analysis is often required for data analyst roles.
What cities in Pennsylvania are hiring for Data Analytics Computer Science jobs? Cities in Pennsylvania with the most Data Analytics Computer Science job openings:
Data Analytics Computer Science jobs near you
Director of Data Analytics & AI

Director of Data Analytics & AI

Penn Community Bank

Perkasie, PA • On-site

Full-time

Posted 26 days ago

Job description

Job description:
Job Title:
Director of Data Analytics and AI
Job Summary: Oversee enterprise data analytics, data governance, business intelligence, and artificial intelligence strategy and operations for the Bank. Lead the development and delivery of secure, compliant, and scalable analytics and AI capabilities that support strategic decision-making, operational efficiency, risk management, and customer experience. Establish and maintain data management, model governance, and AI risk management practices aligned with regulatory expectations and industry standards. Collaborate with business units to implement data-driven solutions while ensuring strong controls over data quality, privacy, model risk, and third-party technology providers.
The scope of responsibility includes enterprise data architecture, data warehousing and reporting platforms, BI tools, advanced analytics, AI/ML solutions, model lifecycle governance, data quality controls, and analytics-related vendor platforms across cloud and on-premises environments.
Essential Functions:
The following is a list of essential functions, which may be subject to change at any time and without advance notice. Management may assign new duties, reassign existing duties, or eliminate a function.
  • Develop and implement the Bank's enterprise data analytics and AI strategy aligned with business goals, risk appetite, and regulatory expectations.
  • Collaborate with the CIO and executive leadership on strategic planning, innovation initiatives, and risk assessments related to data and AI capabilities.
  • Establish and lead a formal data governance framework including data ownership, stewardship, classification, quality standards, lineage, and retention controls.
  • Oversee enterprise reporting, dashboards, and analytics platforms to support finance, risk, operations, compliance, lending, and customer analytics.
  • Lead development and controlled adoption of AI and advanced analytics use cases, ensuring appropriate validation, transparency, monitoring, and human oversight.
  • Implement and maintain model and AI lifecycle controls including development standards, testing, validation support, performance monitoring, change control, and documentation.
  • Partner with Risk, Compliance, and Information Security to align analytics and AI practices with model risk management, privacy, cybersecurity, and consumer protection requirements.
  • Ensure data integrity, accuracy, and completeness across critical reporting and decision-support systems.
  • Oversee data architecture, data warehouse/lake, ETL/ELT pipelines, and analytics tooling across cloud and on-prem environments.
  • Establish standards for responsible AI use, including bias monitoring, explainability, auditability, and appropriate-use controls.
  • Manage analytics and AI vendors, platforms, and data providers, including due diligence, contract review, performance monitoring, and third-party risk coordination.
  • Oversee enterprise change management and release controls for analytics models, reporting logic, and AI-enabled processes.
  • Develop and report analytics program metrics, model performance indicators, and data quality KPIs to executive leadership.
  • Support regulatory exams and internal/external audits involving data management, reporting accuracy, models, and AI usage.
  • Manage departmental budget, staffing, and technology investments related to analytics and AI capabilities.
  • Promote data literacy and analytics adoption across business units through training and stakeholder engagement.

Compliance
  • Comply with all applicable regulations and Bank policies regarding employment and employment law.
  • Participate in annual compliance and other job-related training.
  • Comply with applicable banking regulations, Bank policies and procedures, and supervisory guidance related to data governance, model risk management, AI usage, and third-party risk management.
  • Support regulatory exam, audit, and risk assessment activities related to analytics, reporting, and AI systems.
  • Comply with Bank's internal privacy and ethics standards.

Relationships and Contacts:
  • Internal: Frequent contact with executive leadership, risk management, finance, lending, operations, compliance, and technology teams to support analytics, reporting, and AI initiatives.
  • External: Interaction with data analytics and AI vendors, data providers, consultants, auditors, and regulators.

Education and Experience:
  • Bachelor's degree in Data Science, Analytics, Computer Science, Information Systems, Statistics, or related field. Master's degree preferred.
  • 10+ years of experience in data analytics, business intelligence, data management, or data science roles, with at least 5+ years in leadership.
  • Experience in a regulated industry required; financial services or banking strongly preferred.
  • Experience implementing enterprise analytics, BI, and AI/ML solutions in production environments.

Skills and Competencies:
  • Proven leadership in enterprise analytics, data governance, and AI program development.
  • Strong knowledge of data architecture, data warehousing, BI platforms, and analytics tooling.
  • Proficiency in SQL, Python/R, and data modeling.
  • Experience with modern data platforms (Snowflake, Azure, AWS, Databricks, etc.).
  • Strong familiarity with BI tools (Power BI, Tableau, Qlik).
  • Experience with AI/ML lifecycle management and model governance practices.
  • Demonstrated expertise in model risk management, data privacy, and AI risk considerations within regulated environments.
  • Experience with cloud data and analytics platforms and modern data pipelines.
  • Strong knowledge of data quality management and metadata management practices.
  • Ability to translate business objectives into measurable analytics and AI solutions.
  • Strong project management and vendor management skills.
  • Familiarity with banking regulatory expectations affecting data, reporting, and models.
  • Excellent written and verbal communication skills, including executive-level reporting.
  • Strategic thinker with ability to translate business needs into technical solutions and a focus on controlled innovation and measurable business value.
  • Collaborative and cross-functional leadership approach.
  • Relevant certifications (e.g., CDMP, CBIP, PMP, cloud analytics certifications) are a plus.

Penn community Bank is an equal opportunity employer.

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