Senior Software Developer, Quantitative Solutions

This is a fully remote position, open to applicants in India.

📋 Description

• Oversee the creation and advancement of quantitative data engineering models, which encompass algorithms, data pipelines, and data processing systems, to fulfill business needs.

• Build and sustain data processing pipelines to gather, cleanse, transform, and consolidate large datasets from diverse sources, while ensuring data quality and dependability.

• Design and execute algorithms for data analysis, machine learning, and statistical modeling, employing methods such as regression analysis, clustering, and predictive modeling.

• Identify and apply enhancements to boost the performance and efficiency of data processing and modeling algorithms, taking into account scalability and resource utilization.

• Develop data visualizations and model outputs to effectively convey insights and findings to stakeholders.

• Establish data quality checks and validation procedures to guarantee the accuracy, completeness, and consistency of data utilized in models and analyses.

• Assess the performance of data engineering models through metrics and validation methods, iterating on models to enhance their accuracy and effectiveness.

• Collaborate with data scientists, analysts, and business stakeholders to comprehend requirements, craft models, and provide insights that inform business decisions.

• Document the design, implementation, and evaluation processes of data engineering models, including assumptions, methodologies, and results, to ensure reproducibility and transparency.

• Keep abreast of the latest trends, tools, and technologies in quantitative data engineering and data science, while continually enhancing your skills and knowledge.

⛳️ Requirements

• Proficient in programming languages typically used for data engineering and quantitative analysis, including Python, R, Java, or Scala, alongside experience with SQL for data querying and manipulation.

• Knowledgeable in big data technologies and platforms, such as Hadoop, Apache Kafka, Apache Hive, or AWS EMR, for processing and analyzing extensive datasets.

• Experienced in data visualization techniques and tools, such as Matplotlib, Seaborn, or Tableau, for generating visual representations of data and model outputs to effectively communicate insights.

• Familiar with machine learning frameworks and libraries, such as PyTorch, for implementing and deploying machine learning models.

• Experienced with cloud computing platforms, including AWS, Azure, or Google Cloud Platform, and adept at utilizing cloud services for data engineering and model deployment.

• Strong software development capabilities, including proficiency in software design patterns, version control systems (e.g., Git), and software testing frameworks, to create robust and maintainable code.

• Exceptional problem-solving abilities, with the capacity to analyze intricate data engineering and quantitative analysis challenges, identify solutions, and implement them successfully.

• Excellent communication and collaboration skills, enabling effective work with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand requirements and deliver solutions.

• Domain expertise in fields such as finance, healthcare, or marketing, depending on the industry, to grasp the context and requirements of data engineering models within specific domains.

• A dedication to continuous learning and staying informed about 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