Data Scientist at Blue Sky Analytics · Remote only · 1 - 5 years · Raised funding · Remote only · Posted 24 May 2023

About the Company
Blue Sky Analytics is a Climate Tech startup that combines the power of AI & Satellite data to aid in the creation of a global environmental data stack. Our funders include Beenext and Rainmatter. Over the next 12 months, we aim to expand to 10 environmental data-sets spanning water, land, heat, and more!
We are looking for a data scientist to join its growing team. This position will require you to think and act on the geospatial architecture and data needs (specifically geospatial data) of the company. This position is strategic and will also require you to collaborate closely with data engineers, data scientists, software developers and even colleagues from other business functions. Come save the planet with us!
Your Role
Manage: It goes without saying that you will be handling large amounts of image and location datasets. You will develop dataframes and automated pipelines of data from multiple sources. You are expected to know how to visualize them and use machine learning algorithms to be able to make predictions. You will be working across teams to get the job done.
Analyze: You will curate and analyze vast amounts of geospatial datasets like satellite imagery, elevation data, meteorological datasets, openstreetmaps, demographic data, socio-econometric data and topography to extract useful insights about the events happening on our planet.
Develop: You will be required to develop processes and tools to monitor and analyze data and its accuracy. You will develop innovative algorithms which will be useful in tracking global environmental problems like depleting water levels, illegal tree logging, and even tracking of oil-spills.
Demonstrate: A familiarity with working in geospatial libraries such as GDAL/Rasterio for reading/writing of data, and use of QGIS in making visualizations. This will also extend to using advanced statistical techniques and applying concepts like regression, properties of distribution, and conduct other statistical tests.
Produce: With all the hard work being put into data creation and management, it has to be used! You will be able to produce maps showing (but not limited to) spatial distribution of various kinds of data, including emission statistics and pollution hotspots. In addition, you will produce reports that contain maps, visualizations and other resources developed over the course of managing these datasets.
Requirements
These are must have skill-sets that we are looking for:
- Excellent coding skills in Python (including deep familiarity with NumPy, SciPy, pandas).
- Significant experience with git, GitHub, SQL, AWS (S3 and EC2).
- Worked on GIS and is familiar with geospatial libraries such as GDAL and rasterio to read/write the data, a GIS software such as QGIS for visualisation and query, and basic machine learning algorithms to make predictions.
- Demonstrable experience implementing efficient neural network models and deploying them in a production environment.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Capable of writing clear and lucid reports and demystifying data for the rest of us.
- Be curious and care about the planet!
- Minimum 2 years of demonstrable industry experience working with large and noisy datasets.
Benefits
- Work from anywhere: Work by the beach or from the mountains.
- Open source at heart: We are building a community where you can use, contribute and collaborate on.
- Own a slice of the pie: Possibility of becoming an owner by investing in ESOPs.
- Flexible timings: Fit your work around your lifestyle.
- Comprehensive health cover: Health cover for you and your dependents to keep you tension free.
- Work Machine of choice: Buy a device and own it after completing a year at BSA.
- Quarterly Retreats: Yes there's work-but then there's all the non-work+fun aspect aka the retreat!
- Yearly vacations: Take time off to rest and get ready for the next big assignment by availing the paid leaves.

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We are looking for a skilled Data Scientist to analyze complex datasets, develop predictive models, and generate actionable insights that support business decisions. The ideal candidate should have strong statistical, analytical, and programming skills, along with hands-on experience in machine learning.
Job Description – Data Scientist (Machine Learning & Forecasting)
About the Role
We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, Traditional Statistical Modelling, Forecasting, and Predictive Analytics. The ideal candidate will have hands-on experience building and deploying end-to-end ML solutions, working with large datasets, and translating business problems into scalable data science solutions.
The role requires a strong foundation in statistics, predictive modelling, feature engineering, model evaluation, and time-series forecasting, along with the ability to collaborate with cross-functional teams to deliver business impact.
Key Responsibilities
- Design, develop, and deploy Machine Learning models for business-critical use cases.
- Build and optimize traditional ML models such as:
- Linear Regression
- Logistic Regression
- Decision Trees
- Random Forest
- Gradient Boosting (XGBoost, LightGBM, CatBoost)
- Support Vector Machines
- Clustering Algorithms
- Develop forecasting solutions using:
- ARIMA / SARIMA
- Prophet
- Exponential Smoothing
- Time-Series Regression Models
- Perform exploratory data analysis (EDA), feature engineering, and data validation.
- Evaluate model performance using appropriate statistical and business metrics.
- Work with structured and semi-structured datasets from multiple sources.
- Collaborate with business stakeholders to understand requirements and translate them into analytical solutions.
- Build scalable data pipelines and support model deployment in production environments.
- Monitor model performance, identify data drift, and implement model retraining strategies.
- Present insights and recommendations to technical and non-technical stakeholders.
Required Skills & Qualifications
- Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related quantitative field.
- 5+ years of hands-on experience in Data Science, Machine Learning, and Forecasting.
Technical Skills
Machine Learning
- Strong understanding of supervised and unsupervised learning algorithms.
- Experience with ensemble methods and advanced ML techniques.
- Expertise in model selection, hyperparameter tuning, and performance optimization.
Forecasting & Statistics
- Strong understanding of:
- Time-Series Analysis
- Forecasting Techniques
- Statistical Inference
- Hypothesis Testing
- Probability Distributions
- A/B Testing
Programming
- Advanced proficiency in Python.
- Experience with:
- Pandas
- NumPy
- Scikit-learn
- Statsmodels
- XGBoost / LightGBM
- Prophet
Data & SQL
- Strong SQL skills with experience in complex queries and performance optimization.
- Experience working with large-scale datasets.
Visualization
- Experience with Power BI, Tableau, Matplotlib, Seaborn, or Plotly.
- Cloud & MLOps (Preferred)
- Exposure to AWS, Azure, or GCP.
- Understanding of Docker, Kubernetes, CI/CD, and ML model deployment practices.
Key Competencies
- Strong analytical and problem-solving skills.
- Excellent communication and stakeholder management abilities.
- Ability to work independently in a fast-paced environment.
- Strong business acumen and data-driven decision-making mindset.
Job Description:
As a Data Science Intern, you will collaborate with our data science and analytics teams to work on meaningful projects involving data analysis, predictive modeling, and statistical modeling. You will have the opportunity to apply your academic knowledge in a practical, fast-paced environment, contribute to key data-driven projects, and gain valuable experience with industry-leading tools and technologies.
Responsibilities:
- Assist in collecting, cleaning, and preprocessing data from various sources.
- Perform exploratory data analysis to identify trends, patterns, and anomalies.
- Develop and implement machine learning models and algorithms.
- Create data visualizations and reports to communicate findings to stakeholders.
- Collaborate with team members on data-driven projects and research.
- Participate in meetings and contribute to discussions on project progress and strategy.
- Work with large datasets to clean, preprocess, and analyze data.
- Build and deploy statistical and machine learning models to generate actionable insights.
- Conduct exploratory data analysis (EDA) to uncover trends, patterns, and correlations.
- Assist in the creation of data visualizations and dashboards for reporting insights.
- Support the development and improvement of data pipelines and algorithms.
- Collaborate with cross-functional teams to understand data needs and translate them into actionable analytics solutions.
- Contribute to the documentation and presentation of results, findings, and recommendations.
- Participate in team meetings, brainstorming sessions, and project discussions.
Duration: 03 Months (with the possibility of extending up to 6 months)
MODE: Work From Home (Online)
Requirements:
- Any Graduate / PassOuts / Freasher can apply.
- Currently pursuing a Bachelor's or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
- Proficiency in programming languages such as Python, R, or SQL.
- Strong foundation in statistics, probability, and data analysis techniques.
Benefits
Internship Certificate
Letter of recommendation
Stipend Performance Based
Part time work from home (2-3 Hrs per day)
5 days a week, Fully Flexible Shift
Job Summary:
We are looking for a skilled Data Scientist with strong expertise in demand forecasting, predictive analytics, and emerging Generative AI technologies. The ideal candidate should have hands-on experience in machine learning, deep learning, NLP, and LLM-based solutions, along with proficiency in Python, SQL, Power BI, and advanced Excel. This role involves building scalable forecasting models and leveraging AI/GenAI to deliver actionable business insights.
Key Responsibilities:
- Develop and deploy demand forecasting models using machine learning and deep learning techniques.
- Analyze historical data to identify trends, seasonality, and demand patterns.
- Build predictive models to improve supply chain and inventory planning.
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Required Skills:
- Strong proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).
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- Strong understanding of RAG architectures and vector databases (FAISS, Pinecone, etc.).
- Advanced knowledge of SQL for data manipulation.
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- Strong analytical and problem-solving skills.
Preferred Qualifications:
- Experience in supply chain, logistics, or e-commerce forecasting.
- Knowledge of cloud platforms (AWS, Azure, or GCP).
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Hiring for Data Scientist / Senior Data Scientist
Exp : 4 - 12 yrs
Edu : BE/B.tech/MCA
Work Location : Pune
Notice Period : Immediate - 15 days
Skills :
4+ years of experience in data engineering, data science, or related domains.
Hands-on experience with SQL, Python, and distributed data systems.
Knowledge of machine learning techniques and statistical analysis.
Experience with cloud data platforms (Azure Data Factory, AWS Glue, GCP BigQuery).
Familiarity with DevOps practices and CI/CD for data pipelines.
Platforms & Operations Experience (Preferred)
- Experience working with Azure, AWS, or Google Cloud data tools.
Operational experience with data orchestration tools (Airflow, ADF, Glue).
Understanding of Kubernetes, Docker, or containerized environments.
Hands-on experience with data warehousing platforms (Snowflake, Redshift, BigQuery).
Experience in monitoring, logging, and alerting operations for data workflows.






