Senior Data Scientist

Senior Data Scientist

Overview
We’re building an AI-native Transport Management System (TMS) that replaces fragmented tools (Excel, Samsara, Telegram, etc.) with a single intelligent platform.

At the core:
Fleet optimization
Predictive maintenance
Real-time decision systems
AI Copilot for operations
We’re looking for a Senior Data Scientist who doesn’t just build models—but solves operational problems end-to-end.


What You’ll Do
1. Build Decision Intelligence
Design and deploy models for:
Route optimization (cost per mile, fuel efficiency)
Load → driver → asset matching
Downtime and failure prediction
Translate messy real-world constraints into usable models
2. Work with Real Operational Data
GPS streams, DVIR logs, repair history, fuel transactions
Clean, structure, and validate high-noise datasets
Build feature pipelines from fragmented sources
3. Ship Production-Ready Models
Move beyond notebooks → production systems
Collaborate with backend engineers (API-first mindset)
Monitor model performance and drift
4. Collaborate with Product & Ops
Work directly with fleet managers and dispatchers
Turn vague problems into measurable outcomes
Prioritize impact (cost ↓, downtime ↓, utilization ↑)


What We’re Looking For
Must-Have
5+ years in Data Science / ML
Strong Python (pandas, NumPy, scikit-learn, PyTorch or similar)
Experience with:
Optimization problems (routing, scheduling, assignment)
Time-series / forecasting
Classification & anomaly detection
Experience deploying models (APIs, pipelines, production systems)
Strong Plus
Experience with logistics, supply chain, or mobility
Knowledge of:
Graph algorithms
Operations research (linear programming, heuristics)
Experience working with real-time or streaming data
Mindset
You think in systems, not just models
You care about business impact, not Kaggle scores
You can operate with messy, incomplete data
You challenge assumptions instead of blindly executing


Tech Stack (Current / Planned)
Python (ML + data pipelines)
Laravel (core system)
Node / Python services (AI layer)
Redis, WebSockets
Samsara, EFS, external integrations
Future: feature stores, event streaming, model monitoring


What You’ll Build (Real Examples)
“Which trucks are at risk of failure in next 7 days?”
“What is the cheapest route plan for tomorrow’s loads?”
“Which drivers are underperforming vs fuel benchmarks?”
“Where should we send this truck for repair right now?”


Why Join
Startup speed with real budget and real business problems
Build fast, iterate fast—no bureaucracy, no waiting
Work on real-world optimization, not dashboards
Direct impact on millions in operational costs
Build an AI-native system from the ground up
Ownership: what you build actually ships