logoAiPathly

Analytics Solutions Associate

first image

Overview

The role of an Analytics Solutions Associate at JPMorgan Chase encompasses a diverse set of responsibilities and requirements, varying slightly based on the specific team or department. This overview provides a comprehensive look at the key aspects of the position:

Job Responsibilities

  • Data Management and Analysis:
    • Manage projects related to client profitability data and reporting improvements
    • Conduct root cause analyses on issues impacting client profitability
    • Develop and implement data governance processes
    • Manage data onboarding pipelines
  • Stakeholder Collaboration:
    • Work closely with business and technology stakeholders
    • Partner with senior leaders to translate business requirements into actionable results
  • Project Management:
    • Lead initiatives and maintain project plans
    • Manage milestones, risks, and status reports
  • Communication:
    • Prepare data-driven communications and presentations
    • Develop analytics to inform business health

Required Qualifications

  • Education: Bachelor's degree in Finance, Accounting, Data Science, or related field
  • Experience: 4+ years in financial services, business analytics, or project management
  • Technical Skills: Proficiency in Excel, SQL, Alteryx, and business intelligence tools
  • Analytical Skills: Advanced qualitative and quantitative analysis capabilities
  • Communication: Strong written and verbal communication skills
  • Leadership: Proven project management and team leadership abilities

Preferred Qualifications

  • Advanced technical skills (e.g., Python, AWS, Databricks)
  • Knowledge of data governance and protection
  • Understanding of business process reengineering
  • Prior experience in financial services

Work Environment

  • Typically a hybrid model combining remote and on-site work This role demands a blend of analytical prowess, technical expertise, and strong communication skills, coupled with the ability to manage multiple projects in a fast-paced environment. The ideal candidate will be adept at translating complex data into actionable insights and working collaboratively across various teams and levels of management.

Core Responsibilities

The Analytics Solutions Associate at JPMorgan Chase plays a crucial role in leveraging data to drive business decisions and improve processes. Key responsibilities include:

Data Analysis and Management

  • Coordinate and manage projects related to client profitability data and reporting improvements
  • Conduct in-depth analyses to identify root causes of issues impacting client profitability
  • Develop and implement data governance processes, ensuring data is properly classified, stored, and shared
  • Manage data onboarding pipelines and assist in defining data ownership roles

Stakeholder Collaboration

  • Build and maintain relationships with business stakeholders, project managers, and subject matter experts
  • Work closely with technology partners to deliver proactive solutions and prioritize requests
  • Partner with senior leaders to advance business analytics initiatives

Project Management

  • Lead initiatives and maintain comprehensive project plans
  • Manage milestones, risks, and status reports
  • Drive teams to deliver on initiatives while managing a complex analytics workload

Analytics and Reporting

  • Utilize advanced analytical skills to synthesize large datasets and identify key insights
  • Develop new Intelligent Solutions using tools like Alteryx and Tableau
  • Prepare and distribute data-driven communications and profitability presentations

Strategic Initiatives

  • Define, develop, monitor, and report key management metrics for global operations programs
  • Contribute to operational efficiency, cost modeling, and capacity planning efforts

Technical Expertise

  • Leverage a range of tools including SQL, Excel, Cognos, and SharePoint
  • Develop proficiency in additional technologies such as Qlik Sense, Python, and AWS as needed This role requires a unique blend of analytical skills, technical proficiency, and business acumen. The Analytics Solutions Associate must be able to translate complex data into actionable insights, effectively communicate with various stakeholders, and drive data-driven decision-making across the organization.

Requirements

To excel as an Analytics Solutions Associate at JPMorgan Chase, candidates should possess a combination of education, experience, and skills:

Education

  • Bachelor's degree in a quantitative discipline such as:
    • Finance
    • Accounting
    • Data Science
    • Management Information Systems
    • Business
    • Economics
    • Engineering
    • Statistics
    • Mathematics

Experience

  • Associate level: 4+ years in financial services, business analytics, or project management
  • Senior Associate level: 5+ years in data analysis, Business Intelligence, or Management Consulting

Technical Skills

  • Proficiency in:
    • SQL
    • Excel
    • Tableau or similar visualization tools
    • Alteryx
  • Familiarity with:
    • Python
    • Big data technologies (e.g., Teradata, Snowflake, DataBricks)
    • Cloud platforms (e.g., AWS)
  • Experience with SQL and NoSQL database systems

Analytical and Problem-Solving Skills

  • Strong quantitative and analytical capabilities
  • Ability to analyze large datasets and translate metrics into insights
  • Problem-solving skills with a focus on data-driven solutions

Communication and Project Management

  • Excellent written and verbal communication skills
  • Ability to present complex information to various levels of management
  • Strong project management capabilities
  • Experience with Agile methodologies and tools like Jira

Business Acumen

  • Understanding of financial services industry and business processes
  • Ability to translate business requirements into actionable results
  • Capacity to understand technical systems and their business implications

Interpersonal Skills

  • Ability to build and maintain relationships with diverse stakeholders
  • Strong collaboration and teamwork skills
  • Capacity to influence, negotiate, and manage conflicts

Additional Desirable Qualities

  • Adaptability to a fast-paced, dynamic environment
  • Self-motivation and ability to work independently
  • Attention to detail and commitment to high-quality deliverables The ideal candidate will bring a unique combination of technical expertise, business understanding, and interpersonal skills to drive data-informed decision-making and process improvements across the organization.

Career Development

The role of an Analytics Solutions Associate at JPMorgan Chase offers significant opportunities for professional growth and skill enhancement in data analytics, project management, and business strategy.

Responsibilities and Skill Development

  • Develop intelligent solutions using tools like Alteryx and Tableau
  • Coordinate client profitability data and reporting improvements
  • Conduct root cause analyses for key issues
  • Enhance analytical, critical thinking, and project management skills
  • Improve communication abilities with various stakeholders

Collaboration and Networking

  • Work closely with business and technology stakeholders
  • Build key relationships across different departments and management levels
  • Gain a broader understanding of organizational operations

Professional Growth Opportunities

  • Participate in programs like the Focused Analytics Solutions Team (FAST)
  • Develop creative and practical problem-solving skills in a consulting-style environment
  • Gain exposure to senior leaders and work on high-visibility, strategic projects

Technical Skill Enhancement

  • Improve proficiency in Tableau, Alteryx, SQL, Excel, and potentially Python and Qlik Sense
  • Gain experience with big data technologies and machine learning

Career Progression

  • Potential advancement to roles such as Senior Analyst, Manager, or transition into data science, risk management, or business strategy

Company Culture and Benefits

  • Emphasis on diversity, inclusion, and supportive work environment
  • Comprehensive health care, retirement savings plans, and professional development opportunities

Work Environment

  • Hybrid work model, balancing remote and on-site work for improved work-life balance The Analytics Solutions Associate role at JPMorgan Chase provides a solid foundation for career advancement in data analytics and business strategy, making it an attractive opportunity for those interested in these fields.

second image

Market Demand

The demand for Analytics Solutions Associates, particularly within prestigious financial institutions like JPMorgan Chase, is robust and driven by several factors:

Data-Driven Decision Making

  • Growing need for professionals who can analyze complex data sets
  • Emphasis on developing actionable insights to drive business decisions
  • Increased focus on data strategy, governance, and analytical solutions

Advanced Technology Adoption

  • Financial services sector increasingly adopting big data, machine learning, and cloud technologies
  • Demand for skilled professionals to manage and analyze large datasets
  • Need for expertise in tools like Tableau, Alteryx, and SQL

Cross-Functional Collaboration

  • Roles require effective communication with multiple stakeholders
  • Ability to translate complex technical information for various audiences
  • Project management skills across different functional areas

Strategic and Operational Support

  • Continuous need for analytics solutions in investment banking, consumer and small business banking, commercial banking, and asset management
  • Crucial role in leading daily operations and managing cross-functional programs
  • Importance of ensuring data governance and risk management

Innovation and Talent Development

  • Significant investment in technology by financial institutions
  • Commitment to innovation and talent development
  • Ample opportunities for career growth and learning The demand for Analytics Solutions Associates is driven by the financial sector's increasing reliance on data analytics, adoption of advanced technologies, and the need for skilled professionals to manage complex data sets and drive business decisions.

Salary Ranges (US Market, 2024)

Based on available data and market trends, here's an estimate of salary ranges for Analytics Solutions Associates in the US market as of 2024:

Average Salary

  • Approximately $70,000 to $85,000 per year

Salary Range

  • Typically between $60,000 and $90,000 annually
  • Varies based on experience, location, and other factors

Factors Influencing Salary

  • Education and certifications
  • Years of experience
  • Additional skills (e.g., programming languages, data visualization tools)
  • Geographic location (higher in major tech hubs and financial centers)
  • Company size and industry
  • Data Analyst: Average salary around $84,352, range from $44,000 to $170,000
  • Analytics Associate: Average salary about $71,635, range from $64,394 to $80,650

Career Progression

  • Potential for salary growth with experience and advancement to senior roles
  • Opportunities for bonuses and performance-based incentives in many financial institutions

Benefits and Perks

  • Many employers offer comprehensive benefits packages
  • May include health insurance, retirement plans, and professional development opportunities Note: Salary data is approximate and subject to change. Always research current market rates and consider the total compensation package when evaluating job opportunities.

Data analytics in the financial services sector is rapidly evolving, with several key trends shaping the role of Analytics Solutions Associates:

  1. Data Governance and Strategy: There's an increased focus on establishing robust data governance frameworks and strategies to manage data risk effectively.
  2. Advanced Technologies: The integration of big data, machine learning, and cloud infrastructure is driving business decisions and enhancing customer experiences.
  3. Cross-Functional Collaboration: Analytics professionals must work across various departments, requiring strong communication and project management skills.
  4. Consulting Approach: A problem-solving orientation is essential, involving the development of strategic roadmaps and effective communication of insights to stakeholders.
  5. Customer-Centric Solutions: Analytics solutions are designed to create competitive advantages and improve customer satisfaction through data-driven insights.
  6. Soft Skills Emphasis: Beyond technical expertise, skills such as communication, creativity, and adaptability are highly valued.
  7. Hybrid Work Environment: The industry is adopting flexible work arrangements, combining remote and on-site work.
  8. Innovation and Career Development: There's a strong commitment to fostering innovation and providing opportunities for professional growth and advancement. These trends highlight the dynamic nature of data analytics in finance, emphasizing the need for strategic thinking, technological proficiency, and strong collaborative skills.

Essential Soft Skills

Success as an Analytics Solutions Associate requires a blend of technical expertise and crucial soft skills:

  1. Communication: Ability to present findings clearly and concisely, including data storytelling and translating complex data into actionable insights for non-technical stakeholders.
  2. Problem-Solving: Strong analytical reasoning and innovative thinking to objectively analyze issues and make data-driven decisions.
  3. Interpersonal Skills: Building and maintaining relationships with team members and stakeholders across various departments.
  4. Project Management: Managing multiple projects, prioritizing tasks, and working independently in a fast-paced environment.
  5. Critical Thinking: Making sound judgments and connecting data points to derive meaningful insights for strategic decision-making.
  6. Time Management: Efficiently handling multiple projects simultaneously and keeping them on track.
  7. Client Engagement and Influence: Engaging with clients, influencing business partners, and negotiating across all levels of the organization.
  8. Adaptability: Demonstrating flexibility and creativity in problem-solving, thriving in dynamic environments. These soft skills complement technical abilities, enabling Analytics Solutions Associates to effectively communicate insights, collaborate with stakeholders, and drive business decisions through data-driven solutions.

Best Practices

To ensure the success of analytics solutions, consider the following best practices:

  1. Strategic Data Approach: Align business questions with appropriate data sources, balancing acquisition costs with potential value.
  2. Develop Analytics Products: Focus on scalable solutions that generate measurable financial benefits and improve business performance.
  3. Stakeholder Alignment: Engage stakeholders early to define goals, questions, and KPIs, ensuring analytics efforts align with business objectives.
  4. Build High-Performance Teams: Foster a culture that integrates analytics expertise across business functions, embracing hypothesis-based methodologies.
  5. Enhance Data Literacy: Use descriptive analytics to build understanding and appreciation for data-driven decision-making.
  6. Ensure Compliance and Governance: Adhere to regulations and establish formalized processes for data management.
  7. Continuous Model Refinement: Regularly update analytics models to reflect changing business conditions and new data.
  8. Effective Data Storytelling: Present insights using visuals, context, and narratives that highlight financial benefits and actionable outcomes.
  9. Practical Application: Gain hands-on experience with cloud-based analytics solutions, leveraging resources like AWS Skill Builder and hands-on labs.
  10. Continuous Learning: Stay updated with the latest trends and technologies in data analytics through ongoing education and skill development. By implementing these practices, organizations can create effective, scalable analytics solutions that drive informed decision-making and improve overall performance.

Common Challenges

Analytics Solutions Associates often face several challenges in their role. Here are some common issues and potential solutions:

  1. Data Quality Issues
  • Challenge: Incomplete, inaccurate, or inconsistent data
  • Solution: Implement comprehensive data validation, cleansing techniques, and robust data governance practices
  1. Data Integration
  • Challenge: Difficulty in merging data from various sources
  • Solution: Utilize ETL processes and data integration tools; consider developing a centralized data warehouse or data lake
  1. Resource Constraints
  • Challenge: Limited budgets, compute power, and staffing
  • Solution: Prioritize projects based on ROI; leverage scalable cloud-based solutions
  1. Data Security and Privacy
  • Challenge: Handling sensitive data while adhering to privacy regulations
  • Solution: Implement robust security measures, including encryption and access controls; ensure compliance with data privacy laws
  1. Lack of Domain Knowledge
  • Challenge: Gaps in understanding specific business areas
  • Solution: Collaborate with subject matter experts; conduct domain research and knowledge-sharing sessions
  1. Visualization Complexity
  • Challenge: Creating effective data visualizations, especially for large datasets
  • Solution: Leverage specialized visualization tools; improve data storytelling skills
  1. Scalability and Performance
  • Challenge: Analytics infrastructure struggling with growing data volumes
  • Solution: Adopt distributed computing frameworks or cloud-based solutions that auto-scale
  1. Change Management and Adoption
  • Challenge: Resistance to data-driven decision-making; low team involvement
  • Solution: Communicate the value of analytics; provide training and support; promote a data-driven culture
  1. Unclear Objectives
  • Challenge: Lack of clear goals leading to unfocused analytics efforts
  • Solution: Define specific, measurable objectives aligned with business needs before starting projects By addressing these challenges systematically, Analytics Solutions Associates can enhance the effectiveness of their data analytics operations and drive greater value for their organizations.

More Careers

Clinical Data Manager

Clinical Data Manager

A Clinical Data Manager (CDM) plays a crucial role in the success of clinical trials, ensuring the accuracy, integrity, and compliance of collected data. This overview provides insights into the responsibilities, tools, skills, and impact of CDMs in the healthcare and pharmaceutical industries. Key Responsibilities: - Design and validate clinical databases - Create and implement data management plans - Oversee data processing, from collection to verification - Ensure data quality and regulatory compliance - Prepare reports and analyze trial progress Tools and Software: - Database management systems (e.g., Oracle, Teradata) - Reporting software (e.g., SAP BusinessObjects Crystal Reports) - Clinical trial management software - Analytical software (e.g., IBM SPSS Statistics, SAS) - Categorization software (e.g., Autocoders, Drug coding software) Soft Skills and Qualifications: - Critical thinking and problem-solving abilities - Adaptability and continuous learning - Strong interpersonal and leadership skills - Attention to detail and organizational proficiency Importance and Impact: - Ensure data integrity, crucial for valid clinical trials - Maintain regulatory compliance - Influence the outcome of medical research projects Certification: The Society for Clinical Data Management offers the Certified Clinical Data Manager (CCDM) certification, validating a professional's expertise and contributing to career advancement. CDMs are essential in bridging the gap between raw clinical data and actionable insights, playing a vital role in advancing medical research and drug development.

Clinical Data Readiness Director

Clinical Data Readiness Director

The role of a Clinical Data Readiness Director is crucial in ensuring the integrity, accuracy, and compliance of clinical trial data. This position plays a vital role in the pharmaceutical and biotechnology industries, overseeing the entire data management process for clinical trials. Key responsibilities include: 1. Data Management Oversight: - Design and implement data collection processes - Manage data cleaning and validation - Ensure compliance with regulatory standards (FDA, EMA) 2. Quality and Compliance: - Maintain data integrity and quality - Adhere to Good Clinical Practice (GCP) and ICH guidelines - Execute rigorous quality control procedures 3. Strategic Management: - Oversee clinical data management programs - Manage study budgets and timelines - Communicate progress, risks, and issues to stakeholders 4. Collaboration and Communication: - Coordinate with various teams (clinical research, medical monitors, biostatisticians) - Manage relationships with external partners and vendors 5. Regulatory Documentation: - Contribute to regulatory submissions (e.g., BLA/CTD) - Ensure data meets all necessary regulatory standards 6. Inspection Readiness: - Prepare for and manage regulatory authority inspections Essential skills and expertise include: - In-depth knowledge of clinical research processes and regulations - Proficiency with CDISC data standards and clinical trial databases - Strong understanding of data protection and privacy regulations - Excellent leadership and communication skills The Clinical Data Readiness Director must adapt strategies according to different clinical trial phases (I-IV), focusing on safety data collection, data tool refinement, and post-marketing surveillance as needed. This role is essential for producing high-quality, statistically sound results that inform medical decisions and regulatory approvals in the pharmaceutical and biotechnology sectors.

Clinical Data Sciences Manager

Clinical Data Sciences Manager

Clinical Data Sciences Managers play a crucial role in clinical research, overseeing the management and analysis of data collected during clinical trials. Their responsibilities encompass various aspects of data handling, from database design to final reporting. Here's a comprehensive overview of this role: ### Key Responsibilities - Design and validate clinical databases - Oversee data processing cycles - Generate and resolve data queries - Create data management plans - Implement quality monitoring systems - Prepare data sets and design data collection forms - Analyze data and prepare reports ### Required Skills and Qualifications - Technical proficiency in databases, EDC systems, and statistical software - Strong communication and project management abilities - Analytical and problem-solving skills - In-depth knowledge of regulatory standards ### Education and Experience - Bachelor's degree in a relevant scientific field (master's often preferred) - Professional certifications (e.g., CCDM) are beneficial - Significant experience in clinical data management ### Impact and Importance Clinical Data Sciences Managers ensure data integrity and compliance, which is critical for the success of clinical trials. Their work directly contributes to advancing medical research and improving patient treatments. ### Employment Settings These professionals can work in various organizations, including: - Contract Research Organizations (CROs) - Pharmaceutical and biopharmaceutical companies - Biotechnology firms - Medical device manufacturers - Research institutions and universities - Hospitals By maintaining high standards of data quality and analysis, Clinical Data Sciences Managers play a vital role in the development of new treatments and the advancement of medical science.

Clinical Genomics Scientist

Clinical Genomics Scientist

Clinical Scientists in Genomics play a crucial role in diagnosing, treating, and researching genetic disorders using advanced genetic and genomic technologies. Their work encompasses various aspects of genetic analysis and interpretation, contributing significantly to patient care and scientific advancement. Key Responsibilities: - Perform genetic tests and analyze DNA samples - Interpret and report genomic test results - Conduct research to develop new testing methods - Collaborate with healthcare professionals Educational Requirements: - Bachelor's degree in genetics, molecular biology, or related field - Postgraduate training (e.g., NHS Scientist Training Programme) - Relevant certifications (e.g., Certificate of Completion of Training) Skills and Competencies: - Strong scientific and technical knowledge - Proficiency in data analysis and bioinformatics - Excellent communication and problem-solving skills Career Paths: - Specializations in areas like cancer genomics or rare genetic disorders - Advancement to senior roles in research or clinical settings Work Environment: - Limited direct patient contact - Collaboration within multidisciplinary teams Impact: Clinical Scientists in Genomics significantly influence patient care by providing accurate diagnoses and informing treatment plans. Their work contributes to the advancement of personalized medicine and genetic research.