Data Analyst

We are looking for a detail-oriented and analytical Data Analyst to join our team. The ideal candidate will be responsible for collecting, analyzing, and interpreting data to identify trends, generate insights, and support business decision-making.

The candidate should be comfortable working with large datasets, creating reports and dashboards, and communicating findings clearly to business stakeholders.

Key Responsibilities

• Collect, clean, organize, and analyze data from multiple sources.
• Identify trends, patterns, anomalies, and business opportunities from data.
• Create dashboards, reports, and visualizations for business teams.
• Track and report key performance indicators (KPIs).
• Perform ad-hoc analysis to support business and management decisions.
• Develop and maintain automated reports where possible.
• Work with stakeholders to understand reporting and analytical requirements.
• Ensure data accuracy, consistency, and quality.
• Present analytical findings in a clear and actionable manner.
• Maintain documentation for reports, dashboards, and data processes.

Strong Data Analyst Profile with advanced Excel and SQL expertise

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Mandatory (Experience 1): Must have 4+ years of overall experience as a hands-on Data Analyst

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Mandatory (Tech skill 1): Must be highly proficient in advanced Excel — complex functions, macros, calculations, and pivots

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Mandatory (Tech skill 2): Must have strong hands-on SQL and a good understanding of relational database concepts

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Mandatory (Tech skill 3): Must be able to automate routine tasks using Python (for automation purposes)

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Mandatory (Skill 1): Must have exceptional analytical, problem-solving, and logical skills, with strong attention to detail and accuracy

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Mandatory (Skill 2): Must be able to understand complex data and business logic and convert it into a model (the role models complex utility tariffs, rates, and programs)

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Mandatory (Communication): Must have strong verbal and written communication, able to work independently with India- and US-based team members and articulate problems and solutions over calls and email.

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Mandatory (Location): Must be based locally in Pune (or the nearby Maharashtra belt — Mumbai, Nagpur), as the final round is in person

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Preferred (Domain): Experience in the Energy/Utility industry and familiarity with basic utility (electrical/gas) tariff concepts

We're hiring a Data Analyst to turn raw data into clear, actionable insight. You'll partner with product, sales, marketing, and operations teams to answer their most important questions with data — building dashboards, running deep-dive analyses, and defining the metrics the business runs on. The ideal candidate is fluent in SQL, comfortable wrangling messy datasets, and just as strong at telling the story behind the numbers as they are at producing them. You'll own the accuracy and trustworthiness of the reporting stakeholders rely on to make decisions.

Key Responsibilities

• Design, build, and maintain dashboards and recurring reports across business functions
• Write and optimize SQL queries to extract, join, and transform data from multiple sources
• Run ad-hoc and deep-dive analyses to answer specific business questions
• Define, document, and standardize metrics and KPIs alongside stakeholders
• Investigate data-quality issues and ensure the numbers people see are accurate
• Translate analysis into clear recommendations and present them to non-technical audiences
• Support experimentation and A/B test analysis where relevant
• Automate repetitive reporting to free up time for higher-value analysis

Requirements

• 3+ years in a data analyst or business-intelligence role
• Strong SQL and hands-on experience with Power BI and/or Tableau
• Working knowledge of Python (pandas/numpy) for analysis
• Solid grounding in statistics and analytical methods
• Advanced Excel and strong data-visualization / storytelling skills
• Ability to work independently with stakeholders across functions

Nice to have

• Experience with cloud data warehouses (BigQuery, Snowflake, Redshift)
• Exposure to dbt or other ETL/transformation tooling

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.

Role Overview 

As a Data Scientist, you will work with business stakeholders, AI engineers, and domain experts to transform data into actionable insights and intelligent solutions. You will develop machine learning models, perform statistical analysis, and contribute to AI-driven products that create measurable business impact. 

Key Responsibilities 

Data Science & Machine Learning 

• Analyze structured and unstructured data to identify patterns, trends, and business opportunities.  
• Perform exploratory data analysis (EDA), feature engineering, and data preparation.  
• Develop, evaluate, and optimize machine learning models for prediction, classification, clustering, and forecasting.  
• Apply statistical techniques to solve business problems and validate model performance.  
• Design and execute experiments to improve model accuracy and business outcomes.  

 AI Solution Development 

• Collaborate with AI Engineers, Data Engineers, and domain experts to build AI-powered solutions.  
• Translate business requirements into scalable data science approaches.  
• Contribute to Generative AI and advanced analytics initiatives where applicable.  
• Document methodologies, model performance, and key findings.  

 Required Technical Skills 

• Strong programming skills in Python and SQL for data analysis, feature engineering, and machine learning.  
• Strong understanding of Statistics, Probability, Linear Algebra, and Calculus as applied to machine learning and data science.  
• Experience with Exploratory Data Analysis (EDA), data preprocessing, feature engineering, feature selection, and handling missing or imbalanced data.  
• Good understanding of Supervised, Unsupervised, and Ensemble Machine Learning algorithms, including their assumptions, strengths, limitations, and appropriate use cases.  
• Strong knowledge of Regression, Classification, Clustering, Time Series Forecasting, Dimensionality Reduction, Recommendation Systems, and Anomaly Detection techniques.  
• Experience with Model Evaluation, Cross-Validation, Hyperparameter Optimization, Bias-Variance Trade-off, Feature Importance, Explainable AI (XAI), and Performance Metrics.  
• Understanding of Statistical Inference, Hypothesis Testing, Probability Distributions, Sampling Techniques, Confidence Intervals, and A/B Testing.  
• Experience translating business problems into analytical approaches and developing scalable, data-driven solutions.  
• Working knowledge of Generative AI, Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG) is preferred. 

Preferred Qualifications 

• Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or a related field.  
• 2–4 years of experience developing machine learning or data science solutions.  
• Experience working on end-to-end data science projects in a business environment.  

 Nice to Have 

• Exposure to Generative AI, LLMs, RAG, or Agentic AI.  
• Experience with Computer Vision or Natural Language Processing (NLP).  
• Familiarity with cloud-based AI platforms.  
• Knowledge of construction, engineering, manufacturing, or industrial domains.  
• Participation in hackathons, research, Kaggle competitions, or open-source projects.  

 Soft Skills 

Strong analytical and problem-solving skills, effective communication and collaboration, ownership mindset, adaptability, continuous learning, and a passion for innovation.

Sr.Data Scientist,Python, AI ML

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.

Digital Mold Data Scientist and Manufacturing Analytics Specialist

Job Summary

COAST Systems is seeking a Data Scientist and Manufacturing Analytics Specialist in India to support a global client’s Digital Mold program.

This position will work with large and complex manufacturing, engineering, tooling, maintenance, and quality datasets. The successful candidate will transform fragmented operational data into reliable datasets, dashboards, actionable insights, and continuous-improvement opportunities.

This is a hands-on analytics role requiring close collaboration with engineering, manufacturing, operations, and business stakeholders. The position is particularly suited to someone who can understand a technical manufacturing problem, determine what the data is showing, and communicate practical recommendations that improve performance.

Key Responsibilities

• Collect, prepare, cleanse, normalize, and validate manufacturing and engineering data from multiple sources.
• Establish reliable and repeatable datasets for analytics, reporting, and decision-making.
• Analyze data to identify trends, risks, performance gaps, improvement opportunities, and potential cost savings.
• Develop and maintain dashboards, visualizations, KPI reporting, and business intelligence solutions.
• Analyze maintenance and operational performance using measures such as:
• Mean Time to Repair or MTTR
• Mean Time Between Failures or MTBF
• Overall Equipment Effectiveness or OEE
• Preventive and corrective maintenance performance
• Tool reliability, condition, quality, utilization, and lifecycle indicators
• Work closely with engineering and operations teams to convert technical and operational problems into data-driven solutions.
• Support continuous improvement, operational excellence, and process optimization initiatives.
• Align analyses and recommendations with client goals, priorities, and expected business outcomes.
• Identify relationships among tooling, maintenance, production, quality, sensor, and lifecycle data.
• Present findings clearly to technical and nontechnical stakeholders.
• Help establish consistent data definitions, analytical methods, and reporting standards.
• Support the development of predictive analytics, machine learning, and AI-enabled capabilities where appropriate.
• Learn the COAST software environment and relevant client or third-party systems.
• Help map and connect tool-specific data across systems so that information can be aligned and used consistently.

Required Qualifications

• Bachelor’s or master’s degree in data science, statistics, mathematics, computer science, engineering, operations research, or a related quantitative discipline.
• Strong data science and analytics experience involving large, complex, or multi-source datasets.
• Demonstrated experience with data preparation, cleansing, transformation, normalization, validation, and data-quality management.
• Strong statistical and analytical problem-solving skills.
• Proven experience developing dashboards, data visualizations, KPI reporting, and business intelligence solutions.
• Ability to analyze data and translate findings into clear, practical business or operational recommendations.
• Experience working with technical, engineering, operational, or business stakeholders.
• Strong continuous-improvement and process-optimization mindset.
• Ability to communicate clearly in English with global teams and client stakeholders.
• Ability to work independently, manage priorities, and investigate unclear or incomplete data.
• Strong attention to detail and commitment to data accuracy.

Preferred Qualifications

• Experience analyzing data in a manufacturing, engineering, maintenance, operations, or asset-management environment.
• Understanding of manufacturing equipment, tooling, maintenance, quality, and asset lifecycle concepts.
• Familiarity with MTTR, MTBF, OEE, preventive maintenance, reliability, and related manufacturing KPIs.
• Experience in plastics manufacturing or packaging, including any of the following:
• Injection molding
• Blow molding
• Extrusion blow molding
• Injection stretch blow molding
• Compression molding
• Other polymer-processing operations
• Experience working with cloud-based data platforms or data lake environments.
• Experience combining data from multiple software systems, databases, APIs, files, or vendor platforms.
• Experience with sensor, machine, equipment, IoT, or time-series data.
• Exposure to predictive analytics, machine learning, anomaly detection, forecasting, or AI applications.
• Experience developing analytics that lead to actionable workflows, reduced costs, improved reliability, or reduced manual effort.
• Experience supporting global organizations or working in a client-facing environment.

Technical Skills

Candidates should demonstrate proficiency in several of the following areas:

• SQL
• Python or R
• Statistical analysis
• Data preparation and transformation
• Data validation and data-quality analysis
• Dashboard and visualization development
• Power BI, Tableau, QuickSight, or a comparable BI platform
• Cloud data lakes or cloud analytics environments
• Relational and non-relational data sources
• Advanced Microsoft Excel
• Predictive modeling or machine learning
• API or multi-system data integration

Specific experience with every listed technology is not required. The candidate must, however, have strong foundational analytics skills and the ability to learn unfamiliar platforms and data environments.

Critical Competencies

• Analytical curiosity
• Structured problem-solving
• Systems thinking
• Data accuracy and attention to detail
• Continuous-improvement mindset
• Business and operational awareness
• Clear written and verbal communication
• Cross-functional collaboration
• Client responsiveness
• Adaptability and willingness to learn
• Ability to convert analysis into action

Experience

Approximately 4 to 8 years of relevant professional experience is preferred. Candidates with fewer years may be considered if they demonstrate strong hands-on analytics experience, manufacturing exposure, and the ability to work directly with engineering and operational stakeholders.

What Success Looks Like

The successful candidate will:

• Create trusted and repeatable manufacturing datasets.
• Deliver dashboards and reports that stakeholders actively use.
• Identify meaningful risks, trends, and improvement opportunities.
• Help engineering and operations teams make better decisions from their data.
• Improve the consistency of tool-specific information across systems.
• Progressively develop more advanced predictive and AI-enabled Digital Mold capabilities.
• Produce measurable improvements in reliability, operational performance, cost, and efficiency.

Suggested Key Skills

Data Science, Manufacturing Analytics, Data Analytics, Business Intelligence, Dashboard Development, Data Visualization, Power BI, Tableau, Amazon QuickSight, SQL, Python, R, Statistical Analysis, Data Cleansing, Data Normalization, Data Validation, Data Quality, Manufacturing KPI, OEE, MTTR, MTBF, Predictive Analytics, Machine Learning, Continuous Improvement, Process Optimization, Maintenance Analytics, Reliability Analytics, Cloud Data Lake, Sensor Data, IoT Analytics, Injection Molding, Plastics Manufacturing

Job Summary

We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate should have strong expertise in SQL, Python, Linux, and modern data engineering practices to support data integration, transformation, and analytics.

Key Responsibilities

• Design, develop, and maintain ETL/ELT data pipelines.
• Write efficient and optimized SQL queries for data extraction, transformation, and reporting.
• Develop automation scripts using Python for data processing and workflow optimization.
• Work with Linux environments for deployment, monitoring, and troubleshooting.
• Ensure data quality, integrity, and reliability across data platforms.
• Collaborate with data analysts, software engineers, and business stakeholders to deliver data solutions.
• Monitor, troubleshoot, and optimize data pipelines for performance and scalability.
• Implement best practices for data security, governance, and documentation.

Required Skills

• Strong experience in Data Engineering concepts and ETL/ELT processes.
• Proficiency in SQL, including query optimization and database design.
• Strong programming skills in Python.
• Hands-on experience with Linux commands, shell scripting, and system administration basics.
• Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle.
• Familiarity with Git/version control.
• Strong analytical and problem-solving skills.

Preferred Skills

• Experience with cloud platforms (AWS, Azure, or GCP).
• Knowledge of Apache Spark, Airflow, Kafka, or similar data engineering tools.
• Experience with data warehousing solutions and big data technologies.
• Understanding of CI/CD pipelines and containerization (Docker/Kubernetes).

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• Relevant certifications in cloud or data engineering are an added advantage.

Job Description: 

Join us at Springer Capital, a corporate inclusion training company dedicated to promoting diversity and equity within the workplace.  

Our mission is to transform organizational cultures and achieve justice by creating environments where every individual is valued and feels a sense of belonging. Through providing training for workplace inclusion, understanding microaggressions, mitigating bias, and cultural literacy, Springer Capital seeks to eliminate bias and establish a just, fair working environment.  

As a Data Automation Intern, you will be focusing on researching and developing tools and workflow that automate some parts and processes of our business automation. Since business automation is important throughout the firm, you will have the opportunity to collaborate with various teams across Springer Capital. 

Key Responsibilities:  

• Collect data from various sources, including databases, APIs, and web scraping tools.    
• Clean and process raw data to ensure it is accurate and consistent.     
• Analyze data to extract insights using computational tools, such as Excel, SQL, and Python.   
• Communicate insights in a clear and concise manner with the manager alongside your progress.    
• Implement solutions based on insights you discovered to improve Springer Capital business’ processes or solve problems for client. 

  Qualifications: 

• Passion for Inclusion: A strong commitment to fighting inequality and promoting inclusion in the workplace. 
• Educational Background: Currently enrolled in or recently graduated from a degree program related to social sciences, human resources, business, statistics.  
• Communication Skills: Excellent written and verbal communication skills. Ability to create clear and engaging content. 
• Organizational Skills: Detail-oriented and highly organized. Ability to manage multiple tasks and deadlines effectively. 
• Analytical and Business Software Skills: Proficiency in business software such as Excel, PowerPoint, and Word with a strong preference of knowledge and experience in data analytics  

 Compensation and Expectations: 

• This internship is remote and unpaid. Interns are expected to work 15-20 hours a week. 

Data Engineer Short Hiring Post

🚨 Hiring: Data Engineer

🔹 Experience: 5–9 Years

🔹 Location: Bangalore / Hyderabad

🔹 Skills: PySpark, Python, SQL, ETL, CI/CD, Data Modeling

🔹 Process: L1 Virtual → L2 F2F Karat Test

🔹 F2F: Bangalore / Hyderabad Location

🔹 Positions: Immediate requirement

⚠️ Note: Candidates must be available for F2F Karat immediately after L1.

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