[Hiring] Senior Data Scientist @Charger Logistics Inc

Role Description

We are looking for a Sr. Data Scientist to develop, deploy, and scale machine learning (ML) and AI solutions for fleet analytics, logistics optimization, and operational decision-making. This is a hands-on role focusing on production-grade ML, real-time and streaming analytics, and AI-driven decision systems built on cloud platforms, including Google Cloud, Kafka, and RisingWave.

• Design, develop, and deploy production-grade ML models for fleet optimization, including:
  • Route optimization
  • ETA prediction
  • Fuel efficiency
  • Capacity planning
  • Predictive maintenance
  • Driver behavior analysis
• Build anomaly detection, forecasting, and time-series models to monitor:
  • Vehicle health
  • Trip deviations
  • Fuel theft
  • Demand fluctuations
• Develop batch and real-time ML pipelines with low-latency inference using Kafka, RisingWave, and cloud services.
• Integrate large language models (OpenAI, Google MCP, Ollama, Hugging Face) for:
  • Conversational analytics
  • Automated insights
  • Retrieval-augmented generation (RAG) systems
• Operate MLOps workflows on Google Cloud using:
  • Vertex AI Pipelines
  • Feature Store
  • Model Registry
• Build and optimize end-to-end data pipelines for analytics and ML using:
  • BigQuery
  • Dataflow
  • Dataproc
  • Vertex AI
  • Cloud Functions
  • Pub/Sub
  • Cloud Composer (Airflow)
• Design scalable analytical data models in:
  • BigQuery
  • AlloyDB PostgreSQL
  • Snowflake
• Perform exploratory data analysis (EDA) to uncover trends, anomalies, and business insights.
• Build dashboards and visualizations for stakeholders.
• Collaborate with cross-functional teams to translate business problems into robust data science solutions.
• Support best practices in model development, experimentation, documentation, and data governance.

Qualifications

• Bachelor’s degree or equivalent in Data Analytics, Statistics, Mathematics, or Computer Science.
• 6+ years of hands-on experience in data science and machine learning/AI, delivering production-grade ML solutions.
• Strong experience in Python, including libraries such as:
  • Pandas
  • NumPy
  • Scikit-learn
  • PyTorch
  • TensorFlow
  • XGBoost
  • LightGBM
• Advanced SQL skills, including CTEs, window functions, and query optimization.
• Hands-on experience with Google Cloud, including:
  • Vertex AI (training, pipelines, deployment, feature store)
  • BigQuery (data modeling, performance tuning)
• Experience with streaming platforms (Kafka, RisingWave) and Snowflake.
• Knowledge of anomaly detection, time-series forecasting, optimization, and applied statistical modeling.
• Experience deploying and monitoring ML models in production, including testing, and working with ETL/orchestration tools like Matillion, Airflow, and Cloud Composer.
• Familiarity with advanced ML and AI techniques, including:
  • LLMs
  • Geospatial or graph ML
  • Computer vision
  • GPS data analysis
• Solid understanding of knowledge retrieval patterns including RAG (Retrieval-Augmented Generation), with familiarity of emerging approaches like KAG (Knowledge-Augmented Generation) and CAG (Cache-Augmented Generation).
• Experience with Azure, AWS, GCP, Databricks, or multi-cloud deployments is a plus.
• Excellent communication and problem-solving skills, with the ability to thrive in fast-paced environments.
• Certifications: Google Cloud Professional Data Engineer or Machine Learning Engineer is an asset; SnowPro® Advanced: Data Scientist certification preferred.

Benefits

• Competitive Salary
• Healthcare Benefit Package
• Career Growth