Data Scientist
Weekday AI Bengaluru, Karnataka, India
Technology, Information and Internet · 11-50 employees
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About the role
The Data Scientist will develop and optimize data models and machine learning algorithms to address complex business problems. They are responsible for performing statistical analysis and translating analytical findings into actionable business recommendations.
What they look for
Requirements
Candidates must have at least 2 years of experience and strong proficiency in Python or R. A background in machine learning, statistical methodologies, and data visualization tools is required.
Full description
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.
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 & CompetenciesMust-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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