Data Scientist

Location: Bengaluru, India

Experience: 2 to 4 YOE

• We're looking for a Data Scientist to join our team and help turn one of the richest logistics datasets in the country into models and insights that directly improve how millions of shipments are delivered.
• You'll work on real problems, predicting delivery dates, detecting and resolving delivery failures, estimating live ETAs, building recommendation and anomaly-detection systems, and surfacing insights that drive product and business decisions.
• This is a high-ownership role. We're hiring across the 1 to 4 year range because we care more about how you think and how fast you learn than about years on paper.
• You'll work closely with senior data scientists, engineers, and founders, and you'll own problems end-to-end, from exploring the data to shipping a model to production and measuring its impact.

• Build, train, and evaluate machine learning and deep learning models for real logistics problems, delivery date prediction (EDD), delivery-failure (NDR) resolution, ETA estimation, ranking/recommendations, forecasting, and anomaly detection.
• Explore large, messy, real-world datasets end-to-end: variable identification, data cleaning, feature engineering, dimensionality reduction, distance/similarity computation, and handling missing/imputed data.
• Build and maintain data pipelines (batch & streaming) on Databricks using Spark, PySpark, and Delta Lake.
• Write clean, well-documented code in Python (pandas, NumPy, scikit-learn, Matplotlib) for analysis, modeling, and production.
• Deploy models to production and own their lifecycle, monitoring, validation, drift detection, and continuous improvement.
• Design and run experiments (A/B testing, causal analysis), apply statistical analysis to measure impact, and translate results into actionable recommendations.
• Partner with product, engineering, and business teams to turn ambiguous problems into well-scoped, measurable data science solutions.
• Document methodology and models clearly; communicate findings to both technical and non-technical audiences.

• 1 to 4 years of work experience in data science, machine learning, or a similar role (strong internships and projects count).
• Proficiency in Python, SQL, Spark/PySpark, Artificial Intelligence, and Machine Learning.
• Degree in data science, statistics, engineering, applied mathematics, operations research, information sciences, computer science, or another biological/physical science.
• Knowledge of statistics and machine learning: regression, classification, clustering, and model evaluation.
• Ability to manipulate, analyze, and interpret large datasets.
• Strength in code documentation.
• Proficiency in Git and code versioning tools (GitLab).
• Proficiency in the Atlassian Suite such as JIRA and Confluence.
• Familiarity with cloud computing (AWS, Google Cloud preferred; Azure also relevant).
• Knowledge of dashboarding and visualization tools (Tableau, Power BI, Plotly, Spotfire).
• Strong problem-solving and analytical skills, you can break an ambiguous business problem into a working system.

• Languages: Python, SQL, Java
• Data platforms & big data: Databricks, PySpark, Apache Spark, Delta Lake, structured streaming, Kafka, BigQuery, S3/ADLS, Airflow, Hive, Flink
• ML / DS libraries: pandas, NumPy, scikit-learn, XGBoost; models incl. logistic regression, random forests, SVMs, CNNs/RNNs, transformers, etc.
• Deep learning frameworks: PyTorch, TensorFlow, JAX
• NLP & techniques: tokenization, n-grams, phonetics, fuzzy matching, similarity scoring, embeddings, NER
• GenAI / LLMs: LLMs (GPT, Claude, Llama), prompt engineering, fine-tuning, RAG, LangChain, LlamaIndex, agentic workflows (LangGraph, CrewAI, AutoGen)
• Computer vision: OCR, image segmentation, object detection, ViT/CLIP (nice-to-have)
• Cloud & MLOps: AWS (SageMaker, Bedrock), Google Cloud (Vertex AI), Azure ML, Docker, Kubernetes, FastAPI, CI/CD, feature stores, model registries, model monitoring & drift detection
• Visualization: Tableau, Power BI, Plotly, Spotfire, Matplotlib
• Tooling & collaboration: Git/GitLab, JIRA, Confluence
• Data modeling & governance: star schema / dimensional modeling, data warehousing / lakehouse, data quality, lineage, observability

• Self-motivation and the ability to handle multiple competing priorities in a fast-paced environment.
• Strong interpersonal skills and the ability to build effective relationships with team members, including remotely.
• A bias for ownership and speed, you ship, measure, and iterate.

• Ownership and autonomy: You'll own and drive problems end-to-end, with no micro-management.
• Culture: We value speed and expect you to move fast and stay updated with the latest in ML and AI. People grow extremely fast at ClickPost when they focus on impact and take initiative.
• Our team thrives on transparency.
• Compensation: Competitive salary plus performance bonus.

• Health insurance
• Generous leave policy
• Learning and development budget
• Team events and company offsites
• Company laptop and devices
• Maternity and paternity benefits