Senior Software Developer (Quantitative Solutions)

CFRA Research; India; On-site; INR 2,500,000 - 5,000,000; Full time

Benefits offered by this job

21 days of annual vacation

8 sick days

6 casual days

1 paid Volunteer Day

Medical, Accidental & Term Life Ins.

Telehealth, OPD

Competitive pay

Annual Performance Bonus

Job summary

CFRA Research is seeking a Senior Software Developer to build the next generation of quantitative solutions using a cloud-native stack on AWS. You will help design and implement data pipelines, models, and APIs that power customer-facing analytics platforms.

The role emphasizes collaboration with data scientists and stakeholders, delivering scalable data processing, and staying current with evolving cloud and ML technologies.

Qualifications

• Experience delivering data ingestion, processing, and transformation pipelines.
• Strong knowledge of data quality, validation, and governance.
• Experience applying regression, clustering, and predictive modeling.
• Proficiency in Python, R, SQL, and data querying.
• Ability to communicate complex ideas to stakeholders.

Responsibilities

• Lead design and development of quantitative data models and pipelines.
• Ingest, clean, transform, and aggregate data from multiple sources.
• Design algorithms for data analysis and ML modeling.
• Optimize performance and resource usage of processing systems.
• Create visualizations to communicate insights to stakeholders.
• Implement data quality checks and ensure data integrity.
• Collaborate with data scientists and business stakeholders.
• Document design, implementation, and evaluation for reproducibility.
• Stay updated with trends in data engineering and ML.

Skills

Data Engineering

Quantitative Analysis

Python

R

Java/Scala

SQL

Cloud Computing

Machine Learning

Data Visualization

Communication & Collaboration

Tools

Apache Spark

Apache Flink

AWS Glue

Hadoop

Apache Kafka

Apache Hive

AWS EMR

Tableau

PyTorch

Git

Job description

Description

The Senior Software Developer will be responsible for development of CFRA’s next generation of quantitative solutions using a modern cloud-native technology stack with Python on AWS cloud infrastructure. This is a rare opportunity to make a big impact on both the team and the organization by being part of the initial design and development of a new customer-facing application framework that will serve as the foundation for all future development at CFRA. The ideal candidate has a passion for solving business problems with technology and can effectively communicate business and technical needs to stakeholders. We are looking for candidates that value collaboration with colleagues and having an immediate, tangible impact for a leading global independent financial insights and data company. The team uses a contemporary stack in the AWS cloud to design, build, and maintain robust data delivery pipelines via APIs and Feeds.

Key Responsibilities

• Model Development: Lead the design and development of quantitative data engineering models, including algorithms, data pipelines, and data processing systems, to support business requirements.
• Data Processing: Develop and maintain data processing pipelines to ingest, clean, transform, and aggregate large volumes of data from various sources, ensuring data quality and reliability.
• Algorithm Development: Design and implement algorithms for data analysis, machine learning, and statistical modeling, using techniques such as regression analysis, clustering, and predictive modeling.
• Performance Optimization: Identify and implement optimizations to improve the performance and efficiency of data processing and modeling algorithms, considering factors like scalability and resource utilization.
• Data Visualization: Create visualizations of data and model outputs to communicate insights and findings to stakeholders.
• Data Quality Assurance: Implement data quality checks and validation processes to ensure the accuracy, completeness, and consistency of data used in models and analyses.
• Model Evaluation: Evaluate the performance of data engineering models using metrics and validation techniques, and iterate on models to improve their accuracy and effectiveness.
• Collaboration: Collaborate with data scientists, analysts, and business stakeholders to understand requirements, develop models, and deliver insights that drive business decisions.
• Documentation: Document the design, implementation, and evaluation of data
• engineering models, including assumptions, methodologies, and results, to ensure reproducibility and transparency.
• Continuous Learning: Stay updated with the latest trends, tools, and technologies in quantitative data engineering and data science, and continuously improve your skills and knowledge.

Skills, Knowledge and Expertise

• Data Engineering: Strong background in data engineering principles, including data ingestion, data processing, data transformation, and data storage, using tools and frameworks such as Apache Spark, Apache Flink, or AWS Glue.
• Quantitative Analysis: Proficiency in quantitative analysis techniques, including statistical modeling, machine learning, and data mining, with experience in implementing algorithms for regression analysis, clustering, classification, and predictive modeling.
• Programming Languages: Proficiency in programming languages commonly used for data engineering and quantitative analysis, such as Python, R, Java, or Scala, as well as experience with SQL for data querying and manipulation.
• Big Data Technologies: Familiarity with big data technologies and platforms, such as Hadoop, Apache Kafka, Apache Hive, or AWS EMR, for processing and analyzing large volumes of data.
• Data Visualization: Experience in data visualization techniques and tools, such as Matplotlib, Seaborn, or Tableau, for creating visualizations of data and model outputs to communicate insights effectively.
• Machine Learning Frameworks: Familiarity with machine learning frameworks and libraries, such as PyTorch for implementing and deploying machine learning models. Cloud Computing: Experience with cloud computing platforms, such as AWS, Azure, or Google Cloud Platform, and proficiency in using cloud services for data engineering and model deployment.
• Software Development: Strong software development skills, including proficiency in software design patterns, version control systems (e.g., Git), and software testing frameworks, to develop robust and maintainable code.
• Problem-solving Skills: Excellent problem‑solving skills, with the ability to analyze complex data engineering and quantitative analysis problems, identify solutions, and implement them effectively.
• Communication and Collaboration: Strong communication and collaboration skills, with the ability to work effectively with cross‑functional teams, including data scientists, analysts, and business stakeholders, to understand requirements and deliver solutions.
• Domain Knowledge: Domain knowledge in areas such as finance, healthcare, or marketing, depending on the industry, to understand the context and requirements of data engineering models in specific domains.
• Continuous Learning: A commitment to continuous learning and staying updated with the latest trends, tools, and technologies in data engineering, quantitative analysis, and machine learning.

Benefits

• 21 days of Annual Vacation
• 8 sick days
• 6 casual days
• 1 paid Volunteer Day
• Medical, Accidental & Term Life Insurance
• Telehealth, OPD
• Competitive pay
• Annual Performance Bonus

About CFRA Research

CFRA is a global leader in independent investment insights and data analytics. With a heritage dating back to the 1920s, we provide actionable analytics through a multidisciplinary approach—including forensic accounting, fundamental, and policy research.

Our team of over 90 global analysts provides in-depth qualitative research on 1,600+ companies and 34,000+ funds, quantitative research on over 20,000 global companies. Headquartered in the US with a significant presence across Europe and Asia, CFRA serves over 2,000 clients. We remain committed to providing the independent, differentiated analysis our clients need to make superior investment and business decisions.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.