Senior Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and implement production-quality machine learning models aimed at fleet optimization, including aspects such as route optimization, ETA prediction, fuel efficiency, capacity planning, predictive maintenance, and analysis of driver behavior.

• Create models for anomaly detection, forecasting, and time-series analysis to track vehicle health, identify trip deviations, detect fuel theft, and monitor demand fluctuations.

• Develop both batch and real-time machine learning pipelines that ensure low-latency inference utilizing Kafka, RisingWave, and various cloud services.

• Integrate large language models (such as OpenAI, Google MCP, Ollama, and Hugging Face) to facilitate conversational analytics, automated insights, and retrieval-augmented generation (RAG) systems.

• Manage MLOps workflows on Google Cloud by employing Vertex AI Pipelines, Feature Store, and Model Registry, which assist in model training, deployment, monitoring, and drift detection.

• Construct and enhance comprehensive data pipelines for analytics and machine learning using BigQuery, Dataflow, Dataproc, Vertex AI, Cloud Functions, Pub/Sub, and Cloud Composer (Airflow).

• Design scalable analytical data models in BigQuery, AlloyDB PostgreSQL, and Snowflake; optimize SQL-based feature engineering, data partitioning, and clustering tasks.

• Conduct exploratory data analysis (EDA) to reveal trends, anomalies, and business insights.

• Create dashboards and visualizations tailored for stakeholders.

• Collaborate with cross-functional teams to convert business challenges into effective data science solutions.

• Promote best practices in model development, experimentation, documentation, and data governance.

⛳️ Requirements

• Bachelor’s degree or equivalent in Data Analytics, Statistics, Mathematics, or Computer Science.

• Over 6 years of practical experience in data science and machine learning/AI, delivering production-level machine learning solutions.

• Proficient in Python, including experience with libraries such as Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, XGBoost, and LightGBM.

• Advanced SQL proficiency, encompassing CTEs, window functions, and query optimization techniques.

• Practical experience with Google Cloud, specifically Vertex AI (training, pipelines, deployment, feature store) and BigQuery (data modeling, performance tuning).

• Familiarity with streaming platforms like Kafka, RisingWave, and Snowflake.

• Knowledgeable in anomaly detection, time-series forecasting, optimization, and applied statistical modeling.

• Experience in deploying and monitoring machine learning models in production environments, including testing, and utilizing ETL/orchestration tools like Matillion, Airflow, and Cloud Composer.

• Understanding of advanced machine learning and AI methodologies, including large language models, geospatial or graph machine learning, computer vision, and GPS data analysis.

• Strong grasp of knowledge retrieval frameworks such as RAG (Retrieval-Augmented Generation), with awareness of emerging methodologies like KAG (Knowledge-Augmented Generation) and CAG (Cache-Augmented Generation).

• Experience with Azure, AWS, GCP, Databricks, or multi-cloud deployments is advantageous.

• Exceptional communication and problem-solving abilities, capable of excelling in fast-paced environments.

• Certifications such as Google Cloud Professional Data Engineer or Machine Learning Engineer are beneficial; SnowPro® Advanced: Data Scientist certification is preferred.

🏝️ Benefits

• Competitive Salary

• Healthcare Benefit Package

• Career Growth