SQL Excel Developer

4 weeks ago

Hyderabad, India Alignity Solutions Full time
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If you are a SQL Excel Developer Position looking for excitement, challenge and stability in your work, then you would be glad to come across this page.

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Role:SQL Excel Developer
Location:NYC
Exp: 3 - 5 years

Requirements

We are looking for a highly skilled and motivated Quantitative Developer with experience in building factor scores for custom equity baskets, advanced mathematics, and data automation using Python, SQL, and Excel. The ideal candidate will be proficient in multivariable calculus, statistics, and have a conceptual understanding of fractal mathematics. You will be responsible for building and optimizing quantitative models, automating data flows, and developing Excel-based visualizations. Additionally, you will use your coding expertise to pull data from external websites and integrate it into Excel-based workflows, ensuring smooth data processing and insightful reporting.

Key Responsibilities:

  1. Equity Basket Factor Scoring:

    • Develop and implement factor scoring models for custom equity (stock) baskets.
    • Apply quantitative techniques to select, weight, and aggregate factors that drive equity performance.
    • Work closely with portfolio managers and analysts to refine factor models for specific equity strategies.
    • Conduct backtesting and performance analysis of equity baskets, providing insights for optimization.

  2. Mathematics and Statistical Analysis:

    • Apply advanced mathematical techniques, including multivariable calculus and statistics, to enhance the accuracy and reliability of quantitative models.
    • Use statistical methods to analyze large datasets, derive insights, and validate model assumptions.
    • Familiarize with fractal mathematics at a conceptual level to potentially incorporate fractal analysis into models.
    • Interpret and communicate complex mathematical and statistical findings to stakeholders.

  3. Excel Infrastructure Development:

    • Build and maintain robust Excel infrastructure to support quantitative analysis and reporting.
    • Develop and optimize Excel macros to automate repetitive tasks and workflows.
    • Automate data aggregation and reporting processes using Excel VBA (Visual Basic for Applications).
    • Design and implement advanced Excel visualizations (e.g., charts, tables, bar graphs) and conditional formatting for easy data interpretation.

  4. Data Automation and Integration:

    • Use Python, SQL, and other coding languages to automate data pulls and integration into Excel.
    • Develop scripts and systems to automatically gather and organize data from websites (e.g., Clinicaltrials.gov) or APIs and import it into Excel for analysis.
    • Perform web scraping to aggregate relevant data from external sources and ensure the accuracy of extracted information.

  5. System Documentation and Best Practices:

    • Document system configurations, coding procedures, and best practices for data integration, analysis, and reporting.
    • Maintain clear and accurate documentation of automated workflows, macros, and data processing systems.
    • Create and update user guides and instructions for internal teams on how to leverage tools and systems effectively.

  6. Collaboration and Communication:

    • Collaborate with cross-functional teams, including portfolio managers, quantitative analysts, and IT, to ensure seamless data integration and effective model implementation.
    • Assist in translating complex quantitative models into user-friendly tools for stakeholders.
    • Communicate technical findings and methodologies clearly and effectively to both technical and non-technical team members.

  7. Problem Solving and Optimization:

    • Identify and troubleshoot problems related to data quality, model performance, or automation inefficiencies.
    • Continuously improve and optimize code and infrastructure to increase reliability and speed.
    • Provide solutions to enhance data workflows and address any issues or bugs that arise in the system.

Required Skills and Qualifications:

  • Education:

    • Bachelor's degree in Computer Science, Engineering, Mathematics, Finance, or a related field. Advanced degree (Master's or PhD) preferred but not required.

  • Experience:

    • Minimum [X] years of experience in quantitative analysis, data automation, and financial modeling.
    • Proven experience building factor scores and custom equity baskets for portfolio optimization.
    • Strong proficiency in using Excel for advanced calculations, macros, automation, and data visualization.
    • Experience with web scraping and data extraction from websites (e.g., Clinicaltrials.gov).
    • Familiarity with fractal mathematics, at least at a conceptual level, is a plus.

  • Technical Skills:

    • Excel: Proficiency in advanced Excel functions (pivot tables, formulas, conditional formatting, charts, etc.) and VBA (Visual Basic for Applications) to automate tasks and improve data workflows.
    • Programming: Proficiency in Python and SQL, with the ability to write scripts for data extraction, analysis, and integration into Excel-based reports.
    • Data Automation: Experience automating data flows and reporting processes, ensuring data accuracy and efficiency.
    • Web Scraping: Experience using Python libraries (such as BeautifulSoup or Scrapy) to extract data from websites and integrate it into analysis workflows.
    • Mathematical Techniques: Strong understanding of multivariable calculus, advanced statistics, and their applications in financial modeling.
    • Tools: Experience with data visualization tools such as Tableau or Power BI is a plus.

  • Analytical Skills:

    • Strong ability to analyze large datasets, extract insights, and apply mathematical/statistical techniques to drive decision-making.
    • Detail-oriented with a focus on accuracy and consistency in data analysis and reporting.

  • Problem-Solving Skills:

    • Excellent problem-solving abilities to troubleshoot issues in automated workflows and data models.
    • Ability to approach complex challenges systematically and find effective solutions.

  • Communication Skills:

    • Strong written and verbal communication skills.
    • Ability to effectively explain technical concepts and solutions to both technical and non-technical stakeholders.
    • Ability to document complex systems and processes clearly.

Preferred Qualifications:

  • Familiarity with machine learning techniques and algorithms for factor model optimization.
  • Experience with financial data sources, APIs, or platforms.
  • Knowledge of cloud-based tools or platforms for data storage and processing (e.g., AWS, Google Cloud).


BenefitsVisit us at . Alignity Solutions is an Equal Opportunity Employer, M/F/V/D.

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