Senior Data Analyst

7 days ago

Ahmedabad, Gujarat, India Cygnet Infotech Full time

About the Role:

Job Summary: We are seeking a highly skilled Data Scientist to lead our team in driving business growth through data-driven insights.

Responsibilities:

  • Lead Data Science Team: Oversee the development and implementation of data-driven solutions to drive business growth.
  • Design and Develop Data Pipelines: Design, develop, and maintain data pipelines and back-end services for real-time decisions, reporting, optimization, data collection, and related functions.
  • Manage Test Suites: Manage automated unit and integration test suites to ensure high-quality code.
  • Communicate Effectively: Work collaboratively and communicate effectively with a motivated team of engineers and product managers to achieve business objectives.
  • Recommend New Technologies: Experiment with and recommend new technologies that simplify or improve the Microsoft stack.
  • Optimize Model Code: Work closely with Data Scientists to optimize and reengineer model code to be modular, efficient, and scalable, and to deploy models to production.
  • Build Visualizations: Build visualizations to help derive meaningful insights from data.
  • Maintain Data Platform: Maintain and enhance our data and computation platform.
  • Develop Data Quality Solutions: Develop and implement solutions for data quality validation and continuous improvement.
  • Partner with Stakeholders: Partner with data scientists, PMs, engineers, and business stakeholders to understand business and technical requirements, plan and execute projects, and communicate status, risks, and issues.
  • Analyze System and Data Issues: Perform root cause analysis of system and data issues and develop solutions as required.
  • Apply Statistical Techniques: Apply statistical and machine learning techniques to problems like text feedback analysis, customer/user segmentation/classification to understand usage trends and drivers of satisfactions.
  • Design Experiments: Design experiments, analyze results, and produce actionable, trustworthy conclusions from them.
  • Present Findings: Present findings and recommendations to key decision-makers at various management levels.
  • Leverage Data Science: Leverage the Data Science and Machine Learning capabilities to experiment with and establish new ways of driving customer engagement by leveraging data – ultimately resulting in usage and satisfaction growth.
  • Build Data Tools: Build data manipulation, processing, and data visualization tools and share these tools across the team and using Microsoft Technologies.
  • Calculate Variances: Leverage your statistical and computational knowledge to build algorithms for calculating variances.
  • Apply Data Analysis: Apply data analysis, data mining, and data engineering to present data clearly and develop experiments (A/B testing).
  • Ensure Data Quality: Ensure high-quality data and understand how data is generated out experimental design and how these experiments can produce actionable, trustworthy conclusions.
  • Build Data Logging Tools: Work with development teams to build tools for data logging and repeatable data tasks that will accelerate and automate data scientist duties.

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