We are hiring for Data Scientist jobs in Bangalore for professionals with 1 to 4 years of experience in data science, machine learning, statistical analysis, and predictive modelling. Candidates should have practical experience working with Python, SQL, ML algorithms, data preparation, and analytical models to solve real-world business problems.
Job Overview
Job Role: Data Scientist
Experience: 1–4 Years
Location: Bangalore / Bengaluru, Karnataka
Employment Type: Full-Time
Job Category: Data Science / AI & Machine Learning
Salary: Open for the right candidate
Qualification: B.E / B.Tech / M.Tech / MCA / M.Sc / Statistics / Mathematics / Computer Science / Data Science or equivalent
Work Mode: On-site / Hybrid depending on employer requirements
Key Responsibilities
- Collect, clean, transform, and analyse structured and unstructured datasets.
- Develop machine learning and predictive models for business applications.
- Perform exploratory data analysis to identify patterns, trends, correlations, and anomalies.
- Build classification, regression, clustering, forecasting, and recommendation models.
- Write efficient Python and SQL code for data analysis and model development.
- Perform feature engineering, feature selection, and data preprocessing.
- Train, test, validate, and optimize machine learning models.
- Evaluate models using appropriate performance metrics.
- Work with large datasets from databases, APIs, data warehouses, and other sources.
- Develop dashboards, reports, and data visualizations where required.
- Collaborate with Data Engineers, ML Engineers, Business Analysts, Software Developers, and product teams.
- Translate business requirements into measurable data science solutions.
- Document experiments, methodologies, assumptions, model performance, and findings.
- Support model deployment and production monitoring in collaboration with engineering and MLOps teams.
Required Technical Skills
Candidates should have strong working knowledge of Python, SQL, Statistics and Machine Learning.
Practical experience with Python libraries such as Pandas, NumPy, Scikit-learn, Matplotlib and related data science libraries is expected.
Candidates should understand common machine learning techniques, including Linear Regression, Logistic Regression, Decision Trees, Random Forest, Gradient Boosting, XGBoost, clustering, classification and time-series forecasting.
Knowledge of data preprocessing, feature engineering, model validation, hyperparameter tuning, cross-validation and performance evaluation is important.
Data & Database Skills
Candidates should be comfortable writing SQL queries and working with databases such as MySQL, PostgreSQL, SQL Server, Oracle or similar platforms.
Experience handling data using joins, aggregations, subqueries, window functions, data transformations and analytical queries will be valuable.
Exposure to cloud data platforms, data warehouses, or large-scale data processing tools is an added advantage.
Machine Learning & AI Exposure
Depending on the project, candidates may work on:
Predictive Analytics, Customer Segmentation, Recommendation Systems, Demand Forecasting, Fraud Detection, Risk Modelling, Churn Prediction, NLP, Classification, Regression, Anomaly Detection and other machine learning use cases.
Exposure to TensorFlow, PyTorch, NLP, Generative AI, Large Language Models (LLMs), embeddings or vector databases can be advantageous for AI-focused projects but is not mandatory for every opening.
Experience Level – 1 to 2 Years
Candidates with 1–2 years of experience should have a solid foundation in Python, SQL, statistics, and machine learning fundamentals.
Hands-on experience through commercial projects involving data cleaning, exploratory data analysis, feature engineering, model building, and visualization is preferred.
Candidates should be able to explain the business problem, dataset, algorithm selection, model evaluation, and results of projects they have worked on.
Experience Level – 3 to 4 Years
Candidates with 3–4 years of Data Science experience should be capable of independently handling significant parts of the machine learning lifecycle.
They should be comfortable selecting algorithms, designing experiments, optimizing models, analysing large datasets, and communicating analytical findings to technical and business stakeholders.
Experience with model deployment, cloud environments, MLOps, ML pipelines or production machine learning systems will be an advantage.
Preferred Skills
Additional exposure to AWS, Azure, GCP, Databricks, Spark, PySpark, Docker, MLflow, Airflow, Git, Jupyter Notebook, Power BI or Tableau can strengthen the candidate profile.
Knowledge of A/B testing, probability, hypothesis testing, statistical modelling, experimental design and business analytics is also valuable.
Who Can Apply?
Professionals currently working as Data Scientist, Junior Data Scientist, Associate Data Scientist, Machine Learning Analyst, Data Science Analyst, Applied Data Scientist or in a closely related role can apply.
Candidates should have 1 to 4 years of relevant experience and be able to demonstrate practical data science work rather than only theoretical knowledge.
Apply for Data Scientist Jobs in Bangalore
Candidates looking for Data Scientist jobs in Bangalore with 1 to 4 years of experience can submit an updated resume highlighting their technical skills, machine learning projects, datasets handled, algorithms used, and measurable project outcomes.
The selection process may include Python and SQL assessments, statistics and machine learning questions, case studies, coding rounds, project discussions, technical interviews, and HR discussions, depending on the hiring company.
Salary is open for the right candidate and will depend on relevant experience, Data Science expertise, technical skills, interview performance, and employer requirements.