Pune, India
Live, first seen by us 55 days agoWork setup in the employer’s posting: hybridFrom the employer’s posting
Employment type Full-time
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Translate ambiguous business questions into analytical and modeling problems
Run deep exploratory data analysis on complex, noisy, incomplete datasets
Design features and benchmark modeling approaches such as regression and tree-based models
Build modular, reproducible data and modeling pipelines from extraction to inference
Work with engineering teams to productionize models on the Aera platform
translate ambiguous business questions into clear analytical and modeling problems
Perform deep exploratory data analysis (EDA) on complex, noisy, and often incomplete datasets
Design and implement features, select appropriate modeling approaches (e.g., regression, tree-based models, time series, clustering), and benchmark alternatives.
Build end‑to‑end data and modeling pipelines (data extraction, preprocessing, feature generation, model training, evaluation, and inference)
Collaborate with engineering teams to productionize models on the Aera platform
Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
Experience with cloud platforms (AWS, GCP, or Azure) and distributed data frameworks (e.g., Spark).
1–3 years of experience in data science, data analysis, or ML engineering, or equivalent strong project/internship experience.
Strong proficiency in Python for data analysis: pandas, NumPy, and common scientific/ML libraries (e.g., scikit‑learn; familiarity with TensorFlow/PyTorch is a plus).
Solid experience with EDA and statistical analysis; comfortable working in notebooks to iteratively explore data and build intuition.
Experience structuring code into reusable components, applying basic software engineering practices (version control, testing, documentation).
About You • Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field. • 1–3 years of experience in data science, data analysis, or ML engineering, or equivalent strong project/internship experience.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 55
Similar jobs usually come down between day 8 and day 60.
At Aeratechnology, jobs usually come down by about day 44.
From 11,783 similar postings that came down, and 6 of Aeratechnology’s. Coming down is not always a hire.
1 open job
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
• Design and implement features, select appropriate modeling approaches (e.g., regression, tree-based models, time series, clustering), and benchmark alternatives. • Write clean, well-structured Python code and notebooks for interactive analysis, experimentation, and result communication. • Build end‑to‑end data and modeling pipelines (data extraction, preprocessing, feature generation, model training, evaluation, and inference) that are modular, testable, and reproducible.
• 1–3 years of experience in data science, data analysis, or ML engineering, or equivalent strong project/internship experience. • Strong proficiency in Python for data analysis: pandas, NumPy, and common scientific/ML libraries (e.g., scikit‑learn; familiarity with TensorFlow/PyTorch is a plus). • Solid experience with EDA and statistical analysis; comfortable working in notebooks to iteratively explore data and build intuition.
• Solid experience with EDA and statistical analysis; comfortable working in notebooks to iteratively explore data and build intuition. • Good working knowledge of SQL and data manipulation; able to join, aggregate, and transform data from multiple sources. • Experience structuring code into reusable components, applying basic software engineering practices (version control, testing, documentation).
• Exposure to production ML/analytics systems (scheduling, APIs, CI/CD, monitoring). • Experience with cloud platforms (AWS, GCP, or Azure) and distributed data frameworks (e.g., Spark). • Domain experience in supply chain, logistics, or operations.
Complete your application on jobs.lever.co. The employer’s form will show what is required.
Already applied? Track this application
New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Aera Technology is a pioneer in the growing category of Decision Intelligence Platforms and a Leader in the Gartner® Magic Quadrant™ for 2026 – the technology to digitize, augment, and automate decision-making processes with AI and machine learning. Through our AI decision automation platform, Aera Decision Cloud™, we are helping the best-known brands in the world make smarter, faster decisions.
Privately-held and VC-funded, we have a global team of over 400 Aeranauts – and we’re growing. We deliver Decision Intelligence innovation and services that enable enterprises to automate and scale decision making with accuracy and speed. We continue to be the trusted choice of market leaders for our proven ability to generate value and unlock opportunities that were previously unattainable.
• Partner with product and domain experts to translate ambiguous business questions into clear analytical and modeling problems.
• Perform deep exploratory data analysis (EDA) on complex, noisy, and often incomplete datasets; validate data quality, uncover patterns, and frame hypotheses.
• Design and implement features, select appropriate modeling approaches (e.g., regression, tree-based models, time series, clustering), and benchmark alternatives.
• Write clean, well-structured Python code and notebooks for interactive analysis, experimentation, and result communication.
• Build end‑to‑end data and modeling pipelines (data extraction, preprocessing, feature generation, model training, evaluation, and inference) that are modular, testable, and reproducible.
• Collaborate with engineering teams to productionize models on the Aera platform, including packaging, versioning, monitoring, and validation.
• Communicate findings and recommendations clearly to both technical and non‑technical stakeholders using visualizations, written narratives, and live walkthroughs.
• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
• 1–3 years of experience in data science, data analysis, or ML engineering, or equivalent strong project/internship experience.
• Strong proficiency in Python for data analysis: pandas, NumPy, and common scientific/ML libraries (e.g., scikit‑learn; familiarity with TensorFlow/PyTorch is a plus).
• Solid experience with EDA and statistical analysis; comfortable working in notebooks to iteratively explore data and build intuition.
• Good working knowledge of SQL and data manipulation; able to join, aggregate, and transform data from multiple sources.
• Experience structuring code into reusable components, applying basic software engineering practices (version control, testing, documentation).
• Strong analytical thinking and problem‑solving skills, with a bias for clear, data‑backed decision making.
• Exposure to production ML/analytics systems (scheduling, APIs, CI/CD, monitoring).
• Experience with cloud platforms (AWS, GCP, or Azure) and distributed data frameworks (e.g., Spark).
• Domain experience in supply chain, logistics, or operations.
Full-time
Selected passages from the saved posting. Check the full description for conditions and exceptions.
No pay amount identified in the saved description.
Pune, India
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.