Vacancy description
Wenger & Watson
Bombay, भारत
Role Overview :The role involves working with large and diverse datasets, developing robust analytical and machine learning models, generating actionable insights, and collaborating closely with product, engineering, and business https://jobeax.com/link/ZlR3JZToBtLJKlA9 Responsibilities :Data Science & Machine Learning :- Develop, train, validate, and deploy machine learning models to solve complex business and product problems.- Apply supervised and unsupervised learning techniques to structured and unstructured datasets.- Build predictive models for classification, regression, forecasting, recommendation, segmentation, and anomaly detection use cases.- Select appropriate algorithms based on business objectives, data characteristics, and model performance requirements.- Continuously improve model accuracy, scalability, robustness, and https://jobeax.com/link/pBzdUf2GlpKabWhY Analysis & Modelling :- Apply statistical techniques to identify patterns, relationships, trends, and anomalies within large datasets.- Perform hypothesis testing, statistical inference, correlation analysis, and experimentation.- Design and analyse A/B tests and controlled experiments where required.- Develop statistical and mathematical models to support business and product decisions.- Evaluate model assumptions and ensure statistical validity of analytical https://jobeax.com/link/2fJkXLaqP7WnFgof Preparation & Feature Engineering :- Work with data engineering teams to identify and prepare relevant data sources.- Perform data cleaning, preprocessing, transformation, and exploratory data analysis.- Develop meaningful features from raw data to improve model performance.- Handle missing data, outliers, data inconsistencies, and other data-quality challenges.- Build reusable data preparation and feature engineering https://jobeax.com/link/sUW431ZSbKoDUYtE Analytics :- Develop predictive models to forecast business outcomes and identify future trends.- Analyse customer, product, operational, and behavioural data to generate actionable insights.- Identify opportunities for optimization through predictive and prescriptive analytics.- Translate analytical findings into recommendations that can influence business and product https://jobeax.com/link/ubilBvhcWGh03oOw Evaluation & Optimization :- Establish appropriate metrics to evaluate machine learning model performance.- Perform model validation, cross-validation, error analysis, and performance benchmarking.- Tune model hyperparameters and optimize algorithms for improved performance.- Monitor model behaviour and identify model drift or degradation after deployment.- Ensure models balance accuracy, interpretability, scalability, and business https://jobeax.com/link/EbLMWnWtFcwFbNZa & Deployment :- Collaborate with data engineers and software engineers to productionize machine learning models.- Develop production-ready data science solutions using Python and relevant ML frameworks.- Create scalable model pipelines and APIs for integrating ML models into applications.- Support model deployment, monitoring, testing, and lifecycle management.- Follow engineering best practices around version control, testing, documentation, and https://jobeax.com/link/I9x1OigfDmXcpXB1 & Product Analytics :- Partner with Product, Engineering, Business, and Operations teams to understand business problems and translate them into analytical solutions.- Convert complex analytical findings into clear business recommendations.- Present insights and model outcomes to technical and non-technical stakeholders.- Identify new opportunities where data science and machine learning can create measurable business https://jobeax.com/link/YiugocYLrNRr5cgs & Innovation :- Stay current with developments in machine learning, statistical modelling, and data science.- Evaluate new algorithms, frameworks, and modelling techniques.- Conduct proof-of-concepts and experiments to assess new approaches.- Contribute to the development of reusable data science methodologies and best https://jobeax.com/link/wJIgo45kO3tINlTo Skills :- 5 - 10 years of professional experience in Data Science, Machine Learning, Predictive Analytics, or a related field.- Strong programming skills in Python.- Strong understanding of Machine Learning algorithms and statistical modelling.- Experience with supervised and unsupervised learning techniques.- Strong knowledge of feature engineering, model evaluation, validation, and optimization.- Hands-on experience with libraries/frameworks such as Scikit-learn, Pandas, NumPy, and relevant ML frameworks.- Strong understanding of statistical concepts including hypothesis testing, probability, distributions, regression, and experimental design.- Experience working with large datasets and complex data problems.- Strong SQL skills for data extraction, transformation, and analysis.- Experience taking machine learning models from development to production.- Strong analytical and problem-solving capabilities.- Excellent communication and stakeholder management https://jobeax.com/link/ZitjVqvb84V4AOyQ to Have :- Experience with Deep Learning and frameworks such as PyTorch or TensorFlow.- Experience with cloud platforms such as AWS, GCP, or Azure.- Exposure to distributed data processing technologies such as Spark.- Experience with recommendation systems, forecasting, NLP, fraud detection, or anomaly detection.- Knowledge of MLOps, model monitoring, CI/CD, and ML model lifecycle management.- Experience working in a product-based technology environment.- Experience solving large-scale business and customer analytics https://jobeax.com/link/BYScOGmX84tmJEbS :- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative discipline.- Strong hands-on experience applying data science to real-world business problems. (ref:hirist.tech)