Senior Software Developer - Quantitative Solutions

Talent Zone Consultants; Bengaluru; On-site; INR 800,000 - 1,500,000; Full time

Job summary

Talent Zone Consultants is seeking a Senior Software Developer specializing in quantitative solutions in Bengaluru, Karnataka. The role involves designing and developing data engineering models, optimizing data processing pipelines, and implementing algorithms for analysis and machine learning.

The ideal candidate should have 4-6 years of experience, strong programming skills in Python or Java, and familiarity with big data technologies. Continuous learning and collaboration skills are essential.

Qualifications

• Strong background in data engineering principles.
• Proficiency in quantitative analysis techniques, statistical modeling, and machine learning.
• Proficiency in Python, R, Java, or Scala.
• Familiarity with Hadoop, Apache Kafka, or AWS EMR.
• Experience with Matplotlib, Seaborn, or Tableau.
• Familiarity with libraries such as PyTorch.
• Experience with cloud platforms for data engineering.
• Strong software development skills.
• Excellent problem-solving skills.
• Strong communication and collaboration skills.
• Knowledge in finance, healthcare, or marketing.
• Commitment to continuous learning.

Responsibilities

• Lead the design and development of quantitative data engineering models.
• Develop and maintain data processing pipelines.
• Design and implement algorithms for data analysis and machine learning.
• Identify optimizations for data processing and modeling algorithms.
• Create visualizations of data and model outputs.
• Implement data quality checks and validation processes.
• Evaluate the performance of data engineering models.
• Collaborate with data scientists and stakeholders.
• Document design and implementation of models.
• Stay updated with latest trends and tools.

Skills

Data Engineering

Quantitative Analysis

Programming Languages

Big Data Technologies

Data Visualization

Machine Learning Frameworks

Cloud Computing

Software Development

Problem-solving Skills

Communication and Collaboration

Domain Knowledge

Continuous Learning

Tools

Apache Spark

Apache Flink

AWS Glue

Python

R

Java

Scala

SQL

Hadoop

Apache Kafka

Apache Hive

AWS EMR

Matplotlib

Seaborn

Tableau

PyTorch

AWS

Azure

Google Cloud Platform

FastAPI

Job description

Job openings for Senior Software Developer in Bangalore

Senior Software Developer - Quantitative Solutions

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 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 skills and knowledge.

Desired Skills and Experience

• 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 Python, R, Java, or Scala, as well as experience with SQL for data querying and manipulation.
• Big Data Technologies: Familiarity with Hadoop, Apache Kafka, Apache Hive, or AWS EMR for processing and analyzing large volumes of data.
• Data Visualization: Experience with Matplotlib, Seaborn, or Tableau to create visualizations of data and model outputs that communicate insights effectively.
• Machine Learning Frameworks: Familiarity with libraries such as PyTorch for implementing and deploying machine learning models.
• Cloud Computing: Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, including 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 (Git), and 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, enabling effective work with cross-functional teams.
• Domain Knowledge: Knowledge in areas such as finance, healthcare, or marketing, tailored to industry context of data engineering models.
• Continuous Learning: Commitment to continuous learning, staying updated with the latest trends, tools, and technologies in data engineering, quantitative analysis, and machine learning.

Experience

4 - 6 years

Salary

Not disclosed

Industry

IT Software - Application Programming / Maintenance

Qualification

Key skills: PySpark, MLflow, Kafka, Airflow, Fast API, PyTorch