Smart Work Consultants

PravÄh

Futureacad

Arivu Educational Consultants Pvt Ltd

1. College Visits & Orientation-

○ Identify and shortlist colleges across (Chennai & Coimbatore) for periodic visits

○ Conduct orientation sessions to create awareness about professional courses offered.

○ Maintain a structured visit schedule ensuring regular coverage across districts.

○ Track student interest and collect leads during campus visits.

○ Prepare visit reports and update the lead database after each visit.

2. Exam Centre Activities-

○ Coordinate exam centre promotion activities during active exam periods.

○ Liaise with empanelled agencies in (Chennai & Coimbatore) for on-ground execution.

○ Ensure timely distribution of promotional materials at exam centres.

3. Event Coordination-

○ Coordinate and support events conducted across - Chennai & Coimbatore (seminars, career

fairs, awareness drives, felicitation etc.)

○ Liaise with vendors, venues, and internal stakeholders for smooth execution.

○ Manage logistics including material dispatch, manpower, and setup.

○ Ensure brand visibility and proper representation at all events.

○ Post-event reporting - attendance, leads generated, feedback.

4. Offline Marketing-

○ Coordinate all offline marketing activities across - Chennai & Coimbatore (hoardings,

pamphlets, banners, kiosks, etc.)

○ Work with vendors/agencies for timely installation and material distribution

○ Track and report on marketing coverage and effectiveness

○ Identify new offline marketing opportunities in untapped locations/districts

  

### Requirements

Good communication in Tamil/ Kannada & English.

● Prior experience in field marketing / education sector preferred.

● Strong coordination and vendor management skills.

● Willingness to travel extensively across (Chennai & Coimbatore/Bangalore).

  

### Benefits

3,50,000 - 4,00,000

Branch and Centre Promotion

**Location:** New Delhi, India (with frequent travel across India)

**Team:** Engineering

**Reports to:** Founder & CEO

About Pravah
============

Pravah is an AI lab building foundational intelligence for the electric grid. We work directly with state-owned electricity utilities (DISCOMs) to transform their decades of fragmented operational data into deployable, decision-grade intelligence. Our customers include some of the largest DISCOMs in the country, and our work spans demand forecasting (including renewable generation forecasting), weather forecasting, network mapping, and load flow analysis.

About the Role
==============

As a Forward Deployed Engineer at Pravah, you will be the bridge between our customers and our product. You will be embedded directly with DISCOMs across India to understand the realities of how the grid runs. Since we are an early stage startup, there are many situations where you will be expected to handle things which are beyond the scope of this JD, and your problem solving skills will be put to test. This is a role for someone who is equally comfortable writing Python on a flight, to drone mapping a substation, and presenting to Senior Executives and IAS officers. It is unusually broad: applied data work, large-scale data engineering, geospatial analysis, and high-trust customer engagement.

What You Will Do
================

* Travel to DISCOM sites across India and embed with their engineering, planning, and operations teams to understand their data landscape and operational pain points.
* Acquire, clean, and structure large-scale operational datasets: SCADA streams, smart-meter telemetry, GIS networks, billing records, and weather feeds, often spanning multiple years and hundreds of millions of rows.
* Partner with the ML and engineering teams to tune and deploy models for demand forecasting, renewable generation forecasting, network mapping, and load flow analysis, owning the data side and feeding the model side.
* Architect and ship cloud-native data pipelines on GCP, alongside the engineering team, that productionise these models for the customer.
* Work alongside utility leadership on procurement, compliance, and rollout from initial pitch to live deployment.
* Identify product gaps from the field and feed them back to the core engineering team.

What We're Looking For
========================

* A degree in engineering, computer science, or a quantitative discipline. We care far more about your ability to ship than the name on your degree.
* Strong programming fundamentals in Python; comfort with SQL, pandas, and at least one ML framework (scikit-learn, XGBoost, PyTorch).
* Experience working with large, messy real-world datasets and the patience to figure out why they're messy.
* Comfort with cloud infrastructure (GCP or AWS) and modern data tooling.
* Strong written and verbal communication.
* Willingness to travel within India to the DISCOM offices, often at short notice.
* A bias toward ownership. You lead and execute the task with minimal hand-holding.
* A strong problem-solving instinct, including using AI agents and modern tooling intelligently to multiply your output. (Bonus points for shipping fast. Negative points for letting an agent drop the production database).
* Chill, easygoing and a friendly personality. We value people who are genuinely easy to work with and fit well within a tight-knit team.

Nice to Have
============

* Prior exposure to the power, energy, or infrastructure sector.
* Experience with geospatial data (QGIS, GeoPandas, shapefiles, GDB).
* Experience with deploying, managing or building end-to-end software products at scale.

What You Get
============

* Direct, visible impact on India's grid. The systems you build go live with real utilities serving millions of consumers.
* An unusually broad technical scope: data engineering, geospatial, ML collaboration, and infrastructure (frontend, backend, devops, etc), all in one role.
* Opportunity to work with founders and senior team members from Stanford, Yale, and leading technology companies.

Forward Deployed Engineer

**Weather Data Scientist (Numerical Weather Prediction)**
=========================================================

**Working hours:** The team is distributed across India and the US, so expect a few hours of evening overlap with US Pacific Time on most workdays.

**Overview**
------------

### **About Pravāh**

Pravāh is an AI lab building foundational intelligence for the electric grid. We apply modern machine learning to complex physical infrastructure problems spanning grid operations, weather, and geospatial systems.

Our work sits at the intersection of computer vision, physical systems, and large-scale ML, with deployments across utilities in the United States and India. We leverage multimodal data including satellite imagery, LiDAR, and street-level data to build high-fidelity representations of grid assets and their surroundings.

We are backed by Khosla Ventures, Pear VC, and Conviction - some of the most ambitious investors in Silicon Valley.

More about who we are, what we are building, and why we are excited: [Website](https://www.pravah.com/), [Pravāh on Notion](https://pravah.notion.site/).

**The role**
------------

We are hiring a Weather Data Scientist to advance the next generation of weather forecasting systems for India, with strong attention to observational data quality and geospatial consistency. You will work closely with machine learning and software engineers on two core threads:

1. Numerical weather prediction: run regional NWP models to generate high-resolution forecasts and training data.

2. ML-ready datasets: procure, process, and create ML-ready global and regional weather datasets at large scale (high volume, multi-source, long time horizons), with explicit focus on data-sparse regions.

**What you'll work on**
-----------------------

· Build and benchmark next-generation multiscale, regional, and global forecasting systems against reanalysis and observations, with particular focus on nowcasting and extreme events. The work rests on careful treatment of station, radar, satellite, and other observational data, and on geospatial alignment to model grids.

· Run cycling DA–forecast loops end to end lateral boundary conditions, SSTs, soil states, and spin-up at convection-permitting (~1 km) resolution over Indian sub-regions.

· Stand up rigorous forecast verification across deterministic (RMSE, bias, spectra) and probabilistic (CRPS, BSS) metrics.

· Tailor weather prediction models to renewable-sector needs, particularly solar (GHI) and wind generation (100m winds).

· Assist in training AI-based weather prediction models.

· Work at the intersection of physics-based modeling and machine learning hybrid physics–ML systems, learned parameterizations, and emulators.

**Who you are**
---------------

### **Required qualifications**

· A master's or PhD in geophysical sciences, physics, applied mathematics, computer science, statistics, or a related field. A bachelor's degree with 3+ years of relevant research or operational experience is also acceptable.

· Demonstrated depth in numerical weather prediction, evidenced by operational work, model contributions, research projects, publications, or technical reports.

· Hands-on work with limited-area or mesoscale models such as WRF, MPAS, or comparable systems including dynamical cores, physics parameterizations, and boundary-layer/convection schemes configuring and running them end to end (domains, lateral boundaries, physics suites, spin-up and stability), tuning parameterizations, diagnosing systematic biases, and verifying against observations or reanalysis.

· Experience running convection-resolving simulations at high spatial resolution (~1 km).

· Familiarity with existing operational forecasting models (IFS, GFS, BharatFS).

· Experience contributing to or maintaining model code, or holding responsibility in an operational or quasi-operational forecasting pipeline.

· Experience working with TB-scale, high-dimensional observational and modeling datasets (reanalysis, satellite, radar, weather-station, and sounding data) and the geospatial pipework (grids, reprojection, masks) around them.

· Hands-on experience with widely used reference datasets such as ERA5, MERRA-2, IMDAA, IMERG/GPM, and GOES/INSAT/Himawari.

· Practical experience on High Performance Computers (HPCs).

· Fluency in the modern geoscience Python stack: xarray, dask, zarr, netCDF.

· Experience building reproducible, production-grade pipelines.

· Excellent written and verbal communication, including the ability to explain technical work to both domain experts and cross-disciplinary collaborators.

### **Nice to have**

· Prior work on projects specific to Indian geography.

· Familiarity with coupled earth-system models.

· Experience with any of: ensemble and probabilistic forecasting, regional downscaling, or subseasonal-to-seasonal (S2S) prediction.

· Experience working with operational forecasting agencies (IMD, NCMRWF, ECMWF, NOAA, etc.).

· Familiarity with AI-based weather prediction models and data assimilation techniques.

· Comfort using agentic AI tools to accelerate development.

· Publications in respected atmospheric, oceanic, or climate science venues.

**What you'll gain**
--------------------

· Part of development of weather forecasting models deployed for real-time applications.

· Experience working on hard, open-ended problems at the intersection of AI and physical infrastructure.

· Exposure to how teams set priorities and push the frontier of AI weather prediction.

· Close collaboration with a deeply technical team.

**Why this role**
-----------------

This role sits at the frontier of the AI weather revolution, applying modern machine learning to earth system modeling. The next decade of progress in weather and climate prediction will be built by scientists who understand the physics and the data and have learned to wield generative AI. You will work in data-sparse regions where data is heterogeneous, ground truth is incomplete, and progress requires both technical depth and first-principles thinking.

Weather Data Scientist (Numerical Weather Prediction)

**Weather Data Scientist: Data Assimilation**
=============================================

**Working hours:** The team is distributed across India and the US, so expect a few hours of evening overlap with US Pacific Time on most workdays.

**Overview**
------------

### **About Pravāh**

Pravāh is an AI lab building foundational intelligence for the electric grid. We apply modern machine learning to complex physical infrastructure problems spanning grid operations, weather, and geospatial systems.

Our work sits at the intersection of computer vision, physical systems, and large-scale ML, with deployments across utilities in the United States and India. We leverage multimodal data including satellite imagery, LiDAR, and street-level data to build high-fidelity representations of grid assets and their surroundings.

We are backed by Khosla Ventures, Pear VC, and Conviction - some of the most ambitious investors in Silicon Valley.

More about who we are, what we are building, and why we are excited: [Website](https://www.pravah.com/), [Pravāh on Notion](https://pravah.notion.site/).

**The role**
------------

We are hiring a Weather Data Scientist to advance the next generation of weather forecasting systems for India, with strong attention to observational data quality and geospatial consistency. You will work closely with machine learning and software engineers on three core threads:

1. Data assimilation: contribute hands-on to data assimilation for weather forecasting models.

2. ML-ready datasets: procure, process, and create ML-ready global and regional weather datasets at large scale (high volume, multi-source, long time horizons), with explicit focus on data-sparse regions.

**What you'll work on**
-----------------------

· Build and operate a cycling data assimilation pipeline for our operational forecasting models, and produce the high-resolution gridded products it enables downstream.

· Choose, deploy, and adapt a modern DA framework (e.g. JEDI/UFO, GSI, DART, PDAF) for our regional and global needs.

· Develop observation quality control, bias correction (VarBC), and thinning workflows that hold up at operational data volumes and degrade gracefully when feeds drop out.

· Contribute to AI-based data assimilation pipelines.

· Tailor weather prediction models to renewable-sector needs, particularly solar (GHI) and wind generation (100m winds).

· Assist in training AI-based weather prediction models.

· Work at the intersection of physics-based modeling and machine learning—hybrid physics–ML systems, learned parameterizations, and emulators.

**Who you are**
---------------

### **Required qualifications**

· A master's or PhD in geophysical sciences, physics, applied mathematics, computer science, statistics, or a related field. A bachelor's degree with 3+ years of relevant research or operational experience is also acceptable.

· Demonstrated depth in data assimilation, evidenced by operational work, model contributions, research projects, publications, or technical reports.

· Hands-on experience across the DA toolkit: observation operators and error specification; variational (3D-/4D-Var) or ensemble (EnKF, LETKF, EDA) methods; cycling workflows and innovation statistics; and assimilation of satellite, radar, radiosonde, or station observations.

· Hands-on experience with at least one operational DA framework: JEDI/UFO, GSI, DART, PDAF, or an in-house equivalent, including building observation operators and forward models.

· Working knowledge of bias correction (VarBC), adaptive QC, and gross-error rejection.

· Experience contributing to or maintaining assimilation code, or holding responsibility in an operational or quasi-operational forecasting pipeline.

· Experience working with TB-scale, high-dimensional observational and modeling datasets (reanalysis, satellite, radar, weather-station, and sounding data) and the geospatial pipework (grids, reprojection, masks) around them.

· Hands-on experience with widely used reference datasets such as ERA5, MERRA-2, IMDAA, IMERG/GPM, and GOES/INSAT/Himawari.

· Practical experience on High Performance Computers (HPCs).

· Fluency in the modern geoscience Python stack—xarray, dask, zarr, netCDF.

· Experience building reproducible, production-grade pipelines.

· Excellent written and verbal communication, including the ability to explain technical work to both domain experts and cross-disciplinary collaborators.

· Prior work on projects specific to Indian geography.

· Familiarity with coupled earth-system models.

· Experience with any of: ensemble and probabilistic forecasting, regional downscaling, or subseasonal-to-seasonal (S2S) prediction.

· Experience working with operational forecasting agencies (IMD, NCMRWF, ECMWF, NOAA, etc.).

· Familiarity with AI-based weather prediction models and data assimilation techniques.

· Comfort using agentic AI tools to accelerate development.

· Publications in respected atmospheric, oceanic, or climate science venues.

**What you'll gain**
--------------------

· Part of development of weather forecasting models deployed for real-time applications.

· Experience working on hard, open-ended problems at the intersection of AI and physical infrastructure.

· Exposure to how teams set priorities and push the frontier of AI weather prediction.

· Close collaboration with a deeply technical team.

**Why this role**
-----------------

This role sits at the frontier of the AI weather revolution, applying modern machine learning to earth system modeling. The next decade of progress in weather and climate prediction will be built by scientists who understand the physics and the data and have learned to wield generative AI. You will work in data-sparse regions where data is heterogeneous, ground truth is incomplete, and progress requires both technical depth and first-principles thinking.

Weather Data Scientist (Data Assimilation)

Smart Work Consultants is an Indian recruitment firm providing staffing and HR solutions for tech and non-tech roles.

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 " Drive sales targets & revenue growth for residential/commercial projects

 " Lead and manage a team of Sales Executives / Relationship Managers

 " Handle client meetings, site visits & deal closures

 " Develop and execute sales strategies & lead conversion plans

 " Coordinate with marketing team for lead generation campaigns

 " Maintain strong relationships with clients, brokers & channel partners

 " Track sales performance, pipeline & reporting

 " Ensure excellent customer experience throughout the sales cycle

Sales Manager - construction

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If you are passionate about **yarn quality, process optimization, and textile innovation**, this is a great opportunity to grow in a progressive textile environment.

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*  Conduct **research & trials for yarn/product improvement**
*  Analyze and improve **spinning process efficiency & quality**
*  Develop innovative solutions for **cost reduction & productivity enhancement**
*  Coordinate with production and quality teams for process optimization
*  Monitor raw material performance and yarn characteristics
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*  Support implementation of new technologies and process improvements
*  Ensure compliance with quality and customer standards

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If you are strong in process improvement, time & motion study, and productivity enhancement, this is your opportunity to make a real impact on shop-floor performance?

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