Data Scientist

• Perform advanced data analysis and develop sophisticated predictive and prescriptive models: This includes using statistical and machine learning techniques to extract insights from data and develop models that can be used to predict future outcomes or prescribe actions.
• Explore and preprocess data to ensure data quality and suitability for analysis: This includes cleaning, formatting, and transforming data to make it ready for analysis.
• Design and conduct experiments and A/B tests to validate hypotheses and assess model performance: This includes designing experiments to test the effectiveness of different approaches to data analysis and machine learning.
• Develop and deploy machine learning models into production environments: This includes making sure that machine learning models are working properly and that they can be used to make predictions or recommendations in real time.
• Collaborate with other teams to apply data science to solve complex business problems: This includes working with stakeholders to understand their needs, and developing data-driven solutions that can help them achieve their goals.
• Deliver measurable business value through data-driven insights and recommendations: This includes using data science to identify opportunities to improve the business, and developing and implementing solutions that can help the business achieve its goals.
• Conducting data analysis
• Developing data visualizations
• Integrating data with other applications
• Troubleshooting data problems
• Stay abreast of the latest data science advancements and industry trends
• Writing data documentation

Requirements

• Bachelor's degree in computer science, statistics, mathematics or a related field (preferred)
• Minimum 0-3 years of experience in the relevant field.
• Proven experience in ETL/ELT, Oracle Data Integrator (ODI) is preferred.
• Strong analytical thinking and problem-solving capabilities
• Effective communication and interpersonal skills
• Strong SQL queries, data modelling concepts are mandatory.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Experience working with ML/DL frameworks like Scikit-Learn, TensorFlow, Keras, PyTorch, etc
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, proper usage, etc.) and experience with applications.
• Expert knowledge and Experience in working on conventional Computational Linguistics problems such as Syntactic Processing, Word Sense Disambiguation, Context-Free grammar, Lexical Semantics, Quantification, Plurality, etc.
• Experience using statistical computer languages (Python, SQL, etc.) to manipulate data and draw insights from large data sets.

Benefits

• Competitive salary
• Fuel Card
• Health benefits
• Professional development opportunities
• Inclusive work culture & much more