Solution Data Scientists at AiDash

Gurugram, Haryana, India

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Climate Tech, Utilities, InfrastructureIndustries

Requirements

4–5 years of hands-on experience in data science, analytics, or quantitative research
Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or related field
Strong programming skills in Python for data analysis and machine learning
Proficiency in SQL and experience with relational databases
Experience with ML libraries (scikit-learn, pandas, NumPy, Keras, TensorFlow)
Knowledge of statistical methods (clustering, regression, classification) and experimental design
Familiarity with data visualization tools (matplotlib, seaborn, ggplot2, Tableau, or similar)
Exposure to cloud platforms (AWS, GCP, Azure) is a plus
Proven experience with end-to-end model development (from data exploration to deployment)
Track record of delivering actionable insights that influenced business decisions
Strong analytical and problem-solving skills with attention to detail

Responsibilities

Extract, clean, and analyze large datasets from multiple sources using SQL and Python/R
Build and optimize data scraping pipelines to process large-scale unstructured data
Perform statistical analysis and data mining to identify trends, patterns, and anomalies
Develop automated workflows for data preparation and transformation
Conduct data quality checks and implement validation procedures
Build and validate ML models (classification, regression, clustering) using TensorFlow, Keras, and Pandas
Apply feature engineering to enhance accuracy and interpretability
Execute experiments, apply cross-validation, and benchmark model performance
Collaborate on A/B testing frameworks to validate hypotheses
Work on predictive analytics for wildfire risk detection and storm damage assessment
Translate complex business requirements into data science solutions
Develop predictive models and analytical tools that directly support CRIS decision-making
Create interactive dashboards and automated reports for stakeholders
Document methodologies and maintain clean, production-ready code repositories

Skills

SQL

Python

TensorFlow

Keras

Pandas

feature engineering

cross-validation

A/B testing

machine learning

data pipelines

AiDash

AI solutions for infrastructure management and sustainability

About AiDash

AiDash offers AI-driven solutions that assist industries in managing their infrastructure against climate change threats. Their main products include systems for vegetation management, sustainability management, integrity management, and climate risk intelligence, which utilize AI and satellite data to provide actionable insights. AiDash differentiates itself by focusing specifically on the needs of sectors with geographically distributed assets, such as utility and transportation companies. The company's goal is to enhance the efficiency and sustainability of critical infrastructure while reducing costs and risks associated with climate change.

Palo Alto, CaliforniaHeadquarters

2019Year Founded

$98.7MTotal Funding

SERIES_CCompany Stage

Data & Analytics, Energy, AI & Machine LearningIndustries

201-500Employees

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Health Savings Account/Flexible Spending Account

401(k) Retirement Plan

Parental Leave

Paid Vacation

Risks

Growing competition from AI and satellite data companies may impact market share.

Potential regulatory changes could increase compliance costs for AiDash.

Economic downturns may affect AiDash's ability to secure future funding.

Differentiation

AiDash uses satellite data for real-time infrastructure monitoring and management.

Their AI-driven systems reduce vegetation management costs by up to 20%.

AiDash's solutions improve sustainability by cutting land and air costs by 70-90%.

Upsides

Increased adoption of AI solutions by utilities enhances grid reliability and reduces costs.

Successful Series C funding round raised $58.5 million, surpassing initial targets.

Strategic partnerships, like with AccuKnox, enhance data security and compliance.

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