Lead Market Analyticsand Machine Learning
Location: Kochi, India
Domain: Agriculture, food and commodity markets
Experience: 6-9 years
Role purpose
Lead a small Softobiz analytics team supporting Consolidated Food Co (CFCO), a global food supply
chain business that combines direct sourcing, financing, logistics and weekly market reporting. Work
with CFCO’s technology and commercial teams to turn movements in beef and other food markets
into sourcing decisions. Stay hands-on with AI-assisted market research, time series forecasting and
AutoML.
Key responsibilities
- Lead AI-assisted market research. Track prices, production, trade, seasonality, weather, freight
and exchange rates. Use approved AI tools to extract and compare evidence from sources such as
USDA and Meat & Livestock Australia. Require citations, publication dates and analyst sign-off on
material claims.
- Build and validate forecasts. Set horizons that match buying decisions. Benchmark seasonal
baselines and statistical models against machine learning and AutoML (e.g., AutoGluon
TimeSeries). Use rolling backtests that respect data release dates, check for leakage, and explain
forecast error and uncertainty.
- Hand off validated forecasts. Document model inputs, backtests and run instructions. Set forecast
accuracy thresholds, review performance and recommend retraining. Engineering deploys and
operates the production pipeline.
- Deliver insights and coach analysts. Own the weekly market brief and dashboards. Explain what
changed, what may be driving it and what it means for sourcing. Coach analysts, review their work,
and measure whether AI saves research time while maintaining accuracy.
Required qualifications and skills
- 6-9 years in analytics, econometrics or applied ML; a quantitative degree or equivalent experience.
Strong Python, SQL, statistics and time series forecasting.
- Hands-on use of AutoML or automated model tuning. Show how you benchmarked a forecast
against a baseline and used the results to guide a business decision.
- An example of using an LLM in a repeatable research or analytics workflow. Explain what you
checked, how you handled wrong or unsupported output, and how you protected confidential data.
- Experience leading analytical delivery, mentoring others and presenting commercial
recommendations in clear English.
Preferred experience
- Beef, livestock, food procurement or commodity analytics; Power BI or Tableau; reproducible
experiment tracking; retrieval from approved sources or evaluation of LLM outputs.
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