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Detailed JD Data Scientist to develop advanced analytical solutions and machine learning models that drive business value The role focuses on leveraging data applying statistical techniques and building scalable ML models using modern platforms such as Databricks MLflow and Azure ML Skills Mandatory Skills : Azure Machine Learning, Python - Data Science Key Responsibilities Machine Learning Model Development Develop train and deploy machine learning models using Python Databricks Unity Catalog MLflow and workflows Design and implement endtoend ML solutions including data preparation feature engineering model training and evaluation Apply advanced algorithms across supervised unsupervised and deep learning use cases Optimize model performance through hyperparameter tuning model selection and validation techniques Data Engineering Feature Development Perform data extraction transformation and analysis using SQL and PySpark Create and refine features from raw datasets to improve model accuracy and predictive power Ensure data quality by processing cleansing and validating datasets Analytics Insights Conduct exploratory data analysis EDA and data mining to uncover patterns trends and actionable insights Develop analytical models to support strategic and operational decisionmaking Perform ad hoc analysis and respond to business data requests Model Deployment Lifecycle Deploy models using contemporary ML platforms Databricks Azure ML Maintain and enhance existing models ensuring performance and reliability Collaborate with engineering teams for scalable production deployment and monitoring Collaboration Communication Work with crossfunctional stakeholders to identify AIMLdriven opportunities Translate business problems into analytical solutions Communicate findings through presentations dashboards and executive summaries Documentation Governance Maintain clear documentation of models code and analytical processes Ensure reproducibility and adherence to data governance standards Technical Skills Core Skills Strong programming skills in Python Proficiency in SQL PySpark Experience with Databricks MLflow andor Azure ML Handson experience in machine learning model development and deployment Machine Learning Statistics Strong understanding of ML algorithms statistical modeling and data science techniques Experience with libraries such as Scikitlearn TensorFlow Keras XGBoost Expertise in model evaluation optimization and validation techniques MLOps Awareness Good to Have Exposure to ML lifecycle management CICD concepts and model monitoring Understanding of model drift observability and performance tracking Can share your resume to vijay.r@kairostech.com .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.