Data Scientist

Job Title Data Scientist (3-4 Years’ Experience)

Location :(INDIA)Remote(Need based travel)

Role Overview

We are looking for a Data Scientist with 3-4 years of hands-on experience in extracting insights, building predictive models, and working with both structured and unstructured data. The person will collaborate with cross-functional teams to translate business requirements into data solutions, conduct experiments, and support decision making through data analytics.

Key Responsibilities

Collect, clean, and preprocess data from multiple sources (databases, APIs, logs, external datasets).

Perform Exploratory Data Analysis (EDA) to identify trends, patterns, anomalies.

Feature engineering and selection to improve model performance.

Build, test, and validate machine learning / statistical models (regression, classification, clustering, time-series forecasting, etc.).

Deploy or support deployment of models / prototypes to production, or work closely with engineering / ML Ops to do so.

Monitor model performance, perform error analysis, and iterate to improve accuracy and reliability.

Create dashboards, visualizations, and reports to present findings to stakeholders (technical and non-technical).

Work cross-functionally with product / business / engineering teams to understand problem statements and translate them into measurable metrics.

Stay up to date with latest tools, methods, and techniques; suggest improvements in data workflows and processes.

Required Qualifications & Skills

Experience: 3-4 years in data science / analytics / machine learning roles.

Strong programming skills (Python, R, or similar), including working with libraries such as Pandas, NumPy, Scikit-learn.

Good skills in SQL for data querying, working with relational databases.

Experience in feature engineering, model training, validation, cross-validation, hyperparameter tuning.

Familiarity with data visualization tools or libraries (Matplotlib, Seaborn, Plotly, Tableau, Power BI etc.).

Solid understanding of statistics, probability, hypothesis testing, metrics (precision, recall, F1, ROC, etc.).

Ability to communicate technical results and insights clearly to both technical and non-technical stakeholders.

Problem solving mindset; ability to work in ambiguity; attention to detail.

Preferred Skills (Nice to Have)

Experience with unstructured data (text, images) and NLP or computer vision methods.

Knowledge of cloud platforms (AWS, GCP, Azure) and familiarity with their data / ML services.

Experience with big data tools / distributed computing (Spark, Hadoop etc.).

Exposure to ML Ops, model deployment, monitoring, versioning.

Familiarity with advanced modelling techniques (ensemble methods, deep learning) depending on domain needs.

Domain knowledge relevant to the business (e.g. finance, health, e-commerce, etc.).