Data Analyst

Posted 2 Hours Ago
Be an Early Applicant
2 Locations
Remote
100K-350K Annually
Entry level
Artificial Intelligence • HR Tech • Professional Services • Software
The Role
Analyze and transform structured and unstructured data, identify trends, create reports and dashboards, and apply statistical and machine learning techniques. Support AI initiatives, model development, data quality validation, and deployment of analytical solutions. Collaborate with business and technical stakeholders to translate requirements into data-driven applications using .NET technologies, while documenting processes and maintaining analytical outputs.
Summary Generated by Built In

This role is for one of Weekday’s clients
Salary range: Rs 100000 - Rs 350000 (ie INR 1 - 3.5 LPA)

Min Experience: 0+ years
Location: Maharashtra, India, Telangana, India
JobType: full-time

We are looking for a motivated and analytical Data Analyst with 0–2 years of experience to join our team. The ideal candidate will have a strong interest in data analysis, Machine Learning, Artificial Intelligence for Business, and .NET development, with the ability to translate business requirements into meaningful data-driven solutions.

This role is suited for an early-career professional who enjoys working with data, experimenting with analytical and AI techniques, and understanding how technology can solve real-world business problems. You will collaborate with technical and business teams to analyze datasets, develop analytical models, support AI initiatives, and contribute to applications and solutions built around the .NET ecosystem.


RequirementsKey Responsibilities
  • Collect, clean, transform, and analyze structured and unstructured datasets to identify meaningful trends and business insights.
  • Apply statistical and Machine Learning techniques to support forecasting, classification, segmentation, and other analytical use cases.
  • Assist in developing, testing, and improving machine learning models based on business requirements.
  • Work with stakeholders to understand business challenges and identify opportunities where Artificial Intelligence for Business can improve processes, decision-making, customer experience, or operational efficiency.
  • Support the development and integration of data-driven applications using .NET technologies.
  • Collaborate with .NET developers, data scientists, business teams, and other stakeholders to deliver analytical solutions.
  • Perform exploratory data analysis and create reports, dashboards, and visualizations that communicate findings clearly.
  • Validate data quality, identify inconsistencies, and ensure analytical outputs are accurate and reliable.
  • Assist in deploying, monitoring, and maintaining analytical and AI solutions.
  • Document data processes, analytical methodologies, models, and business requirements.
  • Stay updated with emerging developments in Machine Learning, Artificial Intelligence, data analytics, and business technology.
Must-Have Skills
  • Strong foundation in Data Analysis and Machine Learning concepts.
  • Understanding of Artificial Intelligence for Business and practical AI use cases.
  • Knowledge of .NET development, including familiarity with C# and the .NET framework/ecosystem.
  • Ability to work with datasets, perform data cleaning, transformation, and exploratory analysis.
  • Basic understanding of statistics, predictive modeling, and machine learning algorithms.
  • Strong analytical and problem-solving abilities.
  • Ability to understand business requirements and translate them into technical or analytical solutions.
  • Good communication and collaboration skills.
Good-to-Have Skills
  • JavaScript for developing or supporting data-driven applications and visualizations.
  • Python for data analysis, machine learning, automation, and working with libraries such as Pandas or NumPy.
  • R for statistical analysis, data exploration, and modeling.
  • Familiarity with SQL, databases, APIs, data visualization tools, or cloud-based analytics platforms.
  • Academic projects, internships, certifications, or personal projects involving AI, Machine Learning, Data Analytics, or .NET development.
Qualifications

A Bachelor's degree in Computer Science, Information Technology, Data Science, Statistics, Mathematics, Engineering, or a related discipline is preferred. Candidates with strong project-based experience and a demonstrated interest in AI and analytics are encouraged to apply.

Skills Required

  • Strong foundation in data analysis and machine learning concepts
  • Understanding of artificial intelligence for business and practical AI use cases
  • Knowledge of .NET development, including C# and the .NET framework/ecosystem
  • Ability to clean, transform, and explore datasets
  • Basic understanding of statistics, predictive modeling, and machine learning algorithms
  • Strong analytical and problem-solving abilities
  • Ability to translate business requirements into technical or analytical solutions
  • Good communication and collaboration skills
  • JavaScript for data-driven applications and visualizations
  • Python for data analysis, machine learning, automation, Pandas, or NumPy
  • R for statistical analysis, data exploration, and modeling
  • Familiarity with SQL, databases, APIs, data visualization tools, or cloud-based analytics platforms
  • Academic projects, internships, certifications, or personal projects involving AI, machine learning, data analytics, or .NET development
  • Bachelor's degree in computer science, information technology, data science, statistics, mathematics, engineering, or a related discipline
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The Company
Year Founded: 2021

What We Do

Weekday is an AI-powered recruitment platform that helps startups hire top-tier engineering and product talent. By leveraging a massive database of white-collar professionals and advanced outreach tools, the company streamlines the hiring process through automated sourcing, AI-driven resume screening, and white-glove contingency services. Their mission is to modernize recruitment by enabling companies to discover and engage passive candidates efficiently, ensuring high-quality hires for critical roles.

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