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Location
In office (Chennai, Bengaluru)
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 12, 2026. First seen by Alion on Nov 12, 2026. Weekday scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Weekday is an Indian recruitment company that sources software engineers through referrals from other engineers rather than through job advertisements or agency databases. Its model pays working engineers to vouch for former colleagues they rate, turning informal knowledge about who is genuinely good into a searchable candidate pool that companies can hire from. Based in Bengaluru and backed by Y Combinator, the platform has layered AI screening and outbound sourcing on top of that referral network, and sells to startups and technology companies hiring in the Indian market.
Backed by Y Combinator

This role is for one of Weekday’s clients

Min Experience: 2+ years

Location: Bengaluru, Chennai

JobType: full-time

We are looking for a skilled and analytical Data Scientist to derive meaningful insights from large and complex datasets and help businesses make informed, data-driven decisions. In this role, you will apply advanced data mining techniques, statistical analysis, and predictive modelling to solve business challenges and support organisational transformation.

You will be responsible for developing data models, building machine learning solutions, and translating analytical findings into actionable business recommendations. The ideal candidate should have strong programming skills, hands-on experience with machine learning algorithms, and the ability to communicate complex insights to both technical and non-technical stakeholders.

Requirements

Key Responsibilities

  • Develop, implement, and optimise data models and algorithms to address business problems and improve decision-making.
  • Perform data mining, statistical analysis, and predictive modelling to identify trends, patterns, and actionable insights.
  • Design, develop, and deploy machine learning models using algorithms such as K-Nearest Neighbours (KNN), Naïve Bayes, Support Vector Machines (SVM), Decision Trees, and Random Forest.
  • Apply statistical and analytical methodologies, including hypothesis testing, experimental design, and data validation.
  • Use data science tools and programming languages, with hands-on proficiency in Python or R.
  • Work with structured and unstructured data across relational databases and NoSQL or Big Data platforms.
  • Build and maintain dashboards, reports, and data visualisations using tools such as Tableau, Power BI, QlikView, or D3.js.
  • Write efficient scripts and programmes to automate data processing, analysis, and reporting workflows.
  • Collaborate with cross-functional teams to understand business requirements and translate analytical insights into effective business strategies.
  • Present findings, model outcomes, and recommendations clearly to technical teams, business stakeholders, and leadership.
  • Ensure the accuracy, quality, and reliability of data models, analytical outputs, and visualisations.

Required Skills & Competencies

Must-Have Skills

  • Machine Learning
  • Statistical Analysis
  • Python

Good-to-Have Skills

  • K-Nearest Neighbours (KNN)
  • Naïve Bayes
  • Support Vector Machines (SVM)

Additional Skills

  • Strong understanding of machine learning algorithms, statistical techniques, and predictive modelling.
  • Experience with analytical and statistical programming tools such as Python or R.
  • Knowledge of relational database management systems (RDBMS), including Oracle and MS SQL.
  • Familiarity with NoSQL and Big Data technologies such as MongoDB, Cassandra, Hadoop, HBase, and Cloudera.
  • Experience creating dashboards and visualisations using Tableau, Power BI, QlikView, or D3.js.
  • Strong programming, scripting, and problem-solving abilities.
  • Excellent analytical skills, attention to detail, and a passion for data-driven decision-making.
  • Effective verbal and written communication skills.
  • Proficiency in Microsoft Office tools, particularly Excel, PowerPoint, and Word.

Preferred Qualifications

  • Bachelor's degree in Engineering, Computer Science, or a related discipline that emphasises analytical and quantitative thinking.
  • Master's degree in Data Science, Statistics, Computer Science, or a related field is an added advantage.
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