Website:
ecomine.in
Job details:
About Ecomine
Ecomine is an AI/ML-driven mineral exploration company headquartered in Mangalore, building prediction models that fuse geophysical, geochemical, geological, and hyperspectral datasets to de-risk and accelerate mineral targeting for Indian mining lessees and exploration licence holders. Alongside our model-driven exploration practice, we deliver UAV/LiDAR surveys, drone-borne hyperspectral imaging, GIS mapping, IBM-compliant mine planning, and environmental services to clients across iron ore, manganese, bauxite, laterite, limestone, and dimensional stone. We are a DPIIT-recognised deep-tech startup, and our exploration intelligence stack is developed in close collaboration with our sister venture Spectropy, which builds the AI/ML and hyperspectral analytics core. Geoscientists at Ecomine sit at the centre of this stack — owning the field-to-model loop end-to-end.
Role Summary
We are looking for a field-active, data-fluent Geoscientist to own the exploration and reserves workstream across client engagements and to serve as the geological backbone of our AI/ML mineral prediction model. You will lead surface geological mapping campaigns, design and execute exploration programmes, build UNFC-compliant resource and reserve estimates, and — critically — curate, label, and validate the geophysical, geochemical, and geological training data that feeds our prediction engine. The role sits at the intersection of classical field geology and modern geospatial, spectral, and machine-learning workflows. Strong field instincts are non-negotiable, but you should be equally hungry to work with drone-derived datasets, hyperspectral cubes, and supervised learning pipelines.
Key Responsibilities
AI/ML model development support (core responsibility)
- Curate, clean, and structure geophysical (magnetic, gravity, IP/resistivity, radiometric), geochemical (surface sampling, soil/stream sediment, lithogeochemistry, assay), and geological (lithology, structure, alteration, mineralisation) datasets for ingestion into Ecomine's prediction models.
- Label and annotate training datasets — defining positive (mineralised) and negative (barren) zones, validating ground-truth points, and tagging known deposit signatures.
- Co-design feature engineering with the data science team: translate geological knowledge (proximity to faults, alteration halos, host-rock contacts, geochemical anomalies) into model-usable features.
- Validate model outputs in the field — visit predicted high-prospectivity zones, log ground evidence, and feed back observations to iterate model performance.
- Maintain a versioned, well-documented internal data library across commodities and geological terrains.
Field geology & exploration
- Plan and execute surface geological mapping campaigns at 1:1000 to 1:10,000 scales across client lease areas, with focus on iron ore (BIF/laterite), manganese, bauxite, limestone, and dimensional stone deposits.
- Design exploration programmes — pitting, trenching, core/RC drilling layouts — aligned to UNFC G4 → G1 progression and MEMC Rules 2015 obligations.
- Supervise drilling contractors, log core and chip samples, photograph and archive core, and ensure QA/QC on sampling, sample dispatch, and assay returns.
- Conduct structural mapping, lithological logging, alteration mapping, and ore-body characterisation; build cross-sections and long-sections.
Resource & reserve estimation
- Build digital geological models in Surpac / Datamine / Leapfrog / Micromine (or open-source equivalents); generate block models, grade-tonnage curves, and pit-constrained reserves.
- Prepare UNFC-classified resource and reserve statements for IBM submissions, lease auctions, and investor due-diligence packs.
- Reconcile exploration data with prior GSI/MECL/DMG records and erstwhile lessee data where applicable.
Mining plan & statutory deliverables
- Author the geology, exploration, and reserves chapters of Mining Plans, Schemes of Mining, Modification proposals, and Review of Mining Plans (RoMP) for IBM Regional Office submissions.
- Prepare all statutory plans and sections — surface geological plan, borehole location plan, geological cross-sections, lithology plans — to MCDR 2017 (as amended 2021) standards.
- Liaise with RQPs, IBM officers, and state DGM officials during the mining plan appraisal and approval process.
Geospatial & spectral integration
- Work with the UAV/GIS team to translate orthomosaics, DSMs, and LiDAR point clouds into geologically meaningful interpretation layers.
- Collaborate with the Spectropy team on ground-truthing hyperspectral mineral maps — collect field spectra, build local spectral libraries, and validate AI/ML mineral prediction outputs.
- Use ArcGIS / QGIS / Google Earth Engine for prospectivity mapping, structural lineament extraction, and reconnaissance target generation.
Client & business support
- Lead technical scoping calls and field reconnaissance visits for prospective engagements.
- Contribute geological chapters to consulting reports, tender bids (GeM/CPPP), and pitch decks.
- Mentor interns and junior geologists in the exploration team.
Required Qualifications
- M.Sc. / M.Tech in Geology, Applied Geology, Exploration Geology, or Mineral Exploration from a recognised institute (IITs, IIT-ISM Dhanbad, AMD, NGRI, IISc, Presidency, Anna University, Mangalore University, JNU, or equivalent).
- Minimum 2 years of post-qualification experience in mineral exploration with at least one major mineral commodity — preferably iron ore, manganese, bauxite, or limestone.
- Demonstrated experience in surface geological mapping, core logging, and sampling protocols on active exploration or mining projects.
- Hands-on familiarity with at least two of the three core data streams: geophysical surveys, geochemical sampling programmes, geological mapping & logging — including how each dataset is acquired, processed, and integrated.
- Working knowledge of UNFC classification, MEMC Rules 2015, MCDR 2017 (with 2021 amendments), and IBM Mining Plan format (Category A and B).
- Proficiency in at least one mining/geological modelling software: Surpac, Datamine, Leapfrog Geo, Micromine, or RecMin.
- Strong GIS skills — ArcGIS or QGIS — including georeferencing, digitisation, spatial analysis, and map production.
- Comfortable with field instrumentation: Brunton, GPS/DGPS, handheld XRF (Olympus Vanta / Bruker), pH/EC meters.
- Physical fitness for sustained field deployments in hilly, forested, and remote mining terrain (Western Ghats, Bellary-Hospet belt, Odisha-Jharkhand iron ore belt).
- Valid driving licence and willingness to travel 40–60% of the time.
Preferred / Differentiating
- Exposure to AI/ML workflows for mineral prospectivity — Python, scikit-learn, PyTorch, Google Earth Engine, or commercial tools (Targeting ML, GoldSpot).
- Prior experience preparing mining plans submitted to IBM, or having worked under an RQP on Category A leases.
- Experience with hyperspectral or multispectral data for mineral mapping — ASD FieldSpec, AVIRIS-NG, EnMAP, PRISMA, or drone-mounted sensors.
- Familiarity with geophysical data interpretation — Oasis Montaj, Geosoft, or open-source equivalents for magnetic, gravity, IP/resistivity datasets.
- Knowledge of environmental compliance dimensions of exploration — forest clearance, wildlife clearance, EIA/EMP, CRZ.
- Familiarity with Goa iron ore geology (Western Ghats BIF, laterite caps, Khazan land overlays) or South Indian laterite/dimensional stone geology.
- Publications, conference papers, or technical presentations in exploration geology, mineral prospectivity modelling, or data-driven exploration.
- Working knowledge of Kannada, Konkani, or Hindi for field crew supervision.
Tools & Software Stack
Modelling: Surpac, Datamine, Leapfrog Geo, Micromine GIS: ArcGIS Pro, QGIS, Google Earth Engine Geophysics: Oasis Montaj, Geosoft, ResIPy Remote sensing: ENVI, ERDAS Imagine, SNAP Spectral: ViewSpecPro, Spectral Python, custom Spectropy stack ML / data science: Python (pandas, scikit-learn, PyTorch), Jupyter, Git Geostatistics: Snowden Supervisor, Isatis (a plus), PyKrige, GeostatsPy Field: Avenza Maps, FieldMove, GeoLogger, RTK-DGPS workflows Reporting: MS Office, LaTeX, Adobe Illustrator / Inkscape for map finishing
What You'll Get
- Direct ownership of exploration deliverables and of the geological intelligence layer powering our prediction models — not a cog in a 200-person consultancy.
- Front-row seat to India's first generation of AI/ML-driven mineral prospectivity work; co-author opportunities on technical publications and conference papers.
- Pathway to RQP recognition under MCR 1960 Rule 22(c) with Ecomine sponsoring the application once eligibility is met.
- Field exposure across active mining belts — Bellary, Goa, Hospet, Sandur, Odisha — with full travel and per diem coverage.
- Annual L&D budget for short courses (IIT-ISM, AusIMM, SEG, EAGE) and industry conferences.
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