Data Scientist - Machine Learning

Position : Data Scientist

Experience : 2 - 5 Years

Education : BE/B.Tech in Computer Science, Information Technology, Data Science, Artificial Intelligence, or equivalent

About the Role :

We are seeking a highly analytical and results-driven Data Scientist to join our growing analytics team. The ideal candidate will leverage advanced statistical techniques, machine learning methodologies, and geospatial analytics to solve complex business problems, generate actionable insights, and support strategic decision-making. The role requires hands-on expertise in data preprocessing, predictive modeling, feature engineering, model evaluation, and GIS-based analytics, along with the ability to communicate findings effectively to both technical and business stakeholders.

Key Responsibilities :

Machine Learning & Advanced Analytics :

- Design, develop, validate, and deploy machine learning models to address business challenges.

- Apply supervised and unsupervised learning techniques for classification, regression, clustering, forecasting, and anomaly detection.

- Perform feature engineering, model selection, hyperparameter tuning, and optimization to improve model performance.

- Develop scalable analytical solutions aligned with business objectives.

Data Processing & Statistical Analysis :

- Collect, cleanse, transform, and integrate data from multiple sources.

- Conduct exploratory data analysis (EDA) to identify trends, patterns, and opportunities.

- Apply statistical methods, hypothesis testing, regression analysis, and predictive modeling techniques to generate insights.

- Ensure data quality, accuracy, and consistency across analytical workflows.

Geospatial & GIS Analytics :

- Perform spatial analysis using GIS tools and geospatial datasets.

- Analyze location-based data to uncover geographic trends, patterns, and optimization opportunities.

- Develop geospatial models and visualizations to support operational and strategic initiatives.

- Work with spatial databases and GIS frameworks to derive actionable intelligence.

Model Evaluation & Performance Monitoring :

- Evaluate machine learning models using appropriate metrics such as Accuracy, Precision, Recall, F1-Score, ROC-AUC, RMSE, and MAE.

- Conduct model validation, cross-validation, and performance benchmarking.

- Monitor deployed models for drift, degradation, and improvement opportunities.

- Document methodologies, assumptions, and results to ensure reproducibility and governance.

Reporting & Visualization :

- Develop insightful reports, dashboards, and visualizations to communicate analytical findings.

- Support business intelligence initiatives through data-driven storytelling and KPI tracking.

- Recommend actionable solutions based on analytical outcomes and business requirements.

Stakeholder Collaboration :

- Partner with business, product, and technology teams to understand requirements and translate them into analytical solutions.

- Present findings, recommendations, and model outputs to stakeholders in a clear and concise manner.

- Collaborate in cross-functional projects and contribute to data-driven decision-making across the organization.

Required Technical Skills :

Programming & Data Analysis :

- Python

- SQL

- Pandas

- NumPy

Machine Learning & Statistics :

- Scikit-Learn

- Feature Engineering

- Predictive Modeling

- Statistical Analysis

Data Visualization :

- Matplotlib

- Seaborn

- Plotly (preferred)

- Power BI/Tableau (preferred)

GIS & Geospatial Analytics :

- GIS Analytics

- GeoPandas

- Spatial Data Processing

- Geospatial Visualization

- Location Intelligence

Databases :

- MySQL

- PostgreSQL

- SQL Server

- Data Warehousing Concepts

Preferred Qualifications :

- Experience working with geospatial datasets and GIS platforms.

- Exposure to cloud-based analytics environments (AWS, Azure, or GCP).

- Knowledge of MLOps, model deployment, and monitoring frameworks.

- Familiarity with big data technologies such as Spark/PySpark is an added advantage.

- Experience supporting dashboarding and business intelligence initiatives.

Key Competencies :

- Strong analytical and problem-solving abilities.

- Excellent understanding of machine learning algorithms and statistical concepts.

- Ability to work with large and complex datasets.

- Strong communication and presentation skills.

- Ability to translate analytical insights into business recommendations.

- High attention to detail and commitment to data accuracy.

- Collaborative mindset with the ability to work effectively in cross-functional environments.

What Success Looks Like :

- Delivery of high-impact machine learning and analytical solutions.

- Accurate and actionable business insights derived from data.

- Effective utilization of geospatial analytics for business optimization.

- Continuous improvement in model performance and reporting capabilities.

- Strong stakeholder engagement and measurable contribution to business outcomes.

(ref:hirist.tech)