Data Science Trainee

Job Overview:

iFarmer is offering a 6-month Data Science Trainee Program for graduates passionate about applying AI and data science to agriculture. As a trainee, you’ll work with real datasets (agricultural, financial, satellite), build ML models, contribute to LLM-powered solutions, and support geospatial analysis to drive data-informed decisions.

Successful trainees who perform well during the program may be offered a permanent role with standard remuneration at iFarmer.

𝐈𝐦𝐚𝐠𝐢𝐧𝐞 𝐭𝐡𝐢𝐬…
 - What if your code could optimize fertilizer usage to improve yields while reducing costs?
 - What if your analysis could predict market demand and secure a fair price for their harvest?
 - What if your algorithm could unlock credit for a marginal farmer and change their life?
 - What if your LLM-powered chatbot answers farmers’ questions in Bangla instantly?

At 𝐢𝐅𝐚𝐫𝐦𝐞𝐫, these aren’t “what ifs” — this is what we do. From 𝐬𝐚𝐭𝐞𝐥𝐥𝐢𝐭𝐞-𝐛𝐚𝐬𝐞𝐝 𝐟𝐚𝐫𝐦 𝐦𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠, 𝐟𝐞𝐫𝐭𝐢𝐥𝐢𝐳𝐞𝐫 𝐚𝐧𝐝 𝐢𝐧𝐩𝐮𝐭 𝐨𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧, 𝐟𝐚𝐫𝐦𝐞𝐫 𝐜𝐫𝐞𝐝𝐢𝐭 𝐬𝐜𝐨𝐫𝐢𝐧𝐠, and 𝐩𝐫𝐢𝐜𝐞 𝐟𝐨𝐫𝐞𝐜𝐚𝐬𝐭𝐢𝐧𝐠, to 𝐁𝐚𝐧𝐠𝐥𝐚 𝐯𝐨𝐢𝐜𝐞-𝐞𝐧𝐚𝐛𝐥𝐞𝐝 𝐀𝐠𝐫𝐢𝐆𝐏𝐓 𝐩𝐨𝐰𝐞𝐫𝐞𝐝 𝐛𝐲 𝐋𝐋𝐌𝐬 — we’re transforming agriculture in Bangladesh.

We 𝐩𝐫𝐨𝐯𝐢𝐝𝐞 𝐟𝐮𝐥𝐥-𝐬𝐭𝐚𝐜𝐤 𝐬𝐞𝐫𝐯𝐢𝐜𝐞𝐬 𝐭𝐨 𝐦𝐚𝐫𝐠𝐢𝐧𝐚𝐥 𝐟𝐚𝐫𝐦𝐞𝐫𝐬 — access to finance, inputs, advisory, and markets. Our work has been recognized globally, and iFarmer was featured in 𝐅𝐨𝐫𝐛𝐞𝐬 𝐀𝐬𝐢𝐚’𝐬 𝟏𝟎𝟎 𝐭𝐨 𝐖𝐚𝐭𝐜𝐡 (𝟐𝟎𝟐𝟒)!

We’re looking for curious minds who want to 𝐚𝐩𝐩𝐥𝐲 𝐝𝐚𝐭𝐚 𝐬𝐜𝐢𝐞𝐧𝐜𝐞 𝐚𝐧𝐝 𝐀𝐈 𝐭𝐨 𝐫𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬 that truly matter.
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𝐀𝐛𝐨𝐮𝐭 𝐘𝐨𝐮

You’re excited by the idea of solving impactful problems with data. You enjoy turning messy datasets into insights, building models that matter, and learning fast. You’re a team player, hungry to explore modern AI tools, and you care deeply about using technology to improve farmers’ lives in Bangladesh.
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𝐖𝐡𝐚𝐭 𝐘𝐨𝐮’𝐥𝐥 𝐃𝐨
As a 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐓𝐫𝐚𝐢𝐧𝐞𝐞, you will work closely with our Data Science team to:

➔ Analyze and visualize large-scale agricultural, financial, and satellite datasets
➔ Build data pipelines and dashboards to support business decisions
➔ Experiment with 𝐦𝐚𝐜𝐡𝐢𝐧𝐞 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐦𝐨𝐝𝐞𝐥𝐬 for forecasting and risk scoring
➔ Support in developing 𝐋𝐋𝐌-𝐛𝐚𝐬𝐞𝐝 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐬 (𝐥𝐢𝐤𝐞 𝐀𝐠𝐫𝐢𝐆𝐏𝐓 𝐢𝐧 𝐁𝐚𝐧𝐠𝐥𝐚)
➔ Explore 𝐠𝐞𝐨𝐬𝐩𝐚𝐭𝐢𝐚𝐥 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬 using satellite and remote-sensing data
➔ Present insights to make 𝐝𝐚𝐭𝐚-𝐝𝐫𝐢𝐯𝐞𝐧 𝐩𝐫𝐨𝐝𝐮𝐜𝐭 𝐚𝐧𝐝 𝐬𝐭𝐫𝐚𝐭𝐞𝐠𝐲 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧𝐬