SymphonyAI - Lead Data Scientist - Computer Vision

Introduction
About Us :
SymphonyAI is a leading enterprise AI solutions provider helping retailers and manufacturers optimize business operations through advanced analytics, planning, and automation solutions.
Our products support global organizations in improving supply chain efficiency, inventory performance, forecasting accuracy, and customer satisfaction.
We are committed to delivering measurable outcomes for our clients through innovative technology, deep domain expertise, and strong customer partnerships.

Job Summary :
Shelf Intelligence is our core retail execution product, providing automated in-store shelf audits at scale for CPG and retail customers.
Accuracy, consistency, and measurable improvement over time depend on strong feedback loops between production data and the AI/CV models behind the pipeline.
The CV team develops and improves a retail shelf recognition pipeline spanning detection, product recognition, OCR, and spatial / planogram analysis.
This pipeline generates a large volume of scan data, model behavior signals, and RCA outputs.
This role focuses on turning that data into stronger evaluation, clearer failure analysis, better performance reporting, and targeted experiment support.
About The Role

• Build , train & maintain CV Data Science Models and frameworks across detection, recognition, and OCR, with strong statistical rigor in benchmark design and result interpretation.
• Work closely with Global Data Science Team , Engineering team and Implementation teams for Model testing , deployment abd accuracy testings .
  
• Mine scan meta-reports, model behavior logs, and RCA outputs to identify systematic failure modes and improvement opportunities.
• Partner with CV engineers on targeted analyses and experiments, including retrieval evaluation, post-processing analysis, and planogram / compliance-related error analysis.
• Build SQL-based analytics, dashboards, and recurring reports to make model performance observable across releases.
• Support dataset engineering workflows, including data quality analysis, gap analysis, hard-case mining, and benchmark set curation.
  

About You

• ML proficiency in Computer Vision & Deep learning with hands-on exposure to image / CV problems such as classification, detection, embeddings, or OCR.
• Strong Python proficiency, including pandas, numpy, scikit-learn, PyTorch ,TensorFlow ,OpenCV.
• Strong SQL and relational database fundamentals, with experience working directly on large datasets using joins, aggregations, window functions, and query optimization.
• Strong grounding in statistics, including hypothesis testing, sampling, confidence intervals, and experiment design.
  

Good To Have

• Retail / CPG domain familiarity.

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• Experience with dashboarding and observability tools such as Grafana.
• Experience with evaluation tooling or experiment tracking platforms such as MLflow or Weights & Biases.
• Exposure to large-scale production ML systems and MLOps practices.
• Experience communicating analytical findings to technical and non-technical stakeholders.
• Familiarity with cloud data platforms (AWS, GCP, or Azure).
  

About Us
What We Offer :

• Competitive salary and benefits package.
• Opportunity to work on high-impact retail forecasting and supply chain programs.
• Exposure to leading global retailers and advanced AI-driven planning solutions.
• A collaborative and fast-paced work environment.
• Learning and growth opportunities across retail, supply chain, and data science domains.
  

(ref:hirist.tech)