Work with stakeholders to understand their needs and translate them into technical requirements: This includes understanding the business goals of the stakeholders, and identifying the data that is needed to achieve those goals.
Develop and implement data science solutions: 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.
Evaluate the performance of data science solutions: This includes tracking the accuracy of predictions and the effectiveness of recommendations.
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.
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.
Mentor and guide data scientists and promote knowledge sharing: This includes sharing knowledge and expertise with other data scientists, and helping them develop their skills and knowledge.
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
Promote the use of data science within the organization
Bachelor's degree in computer science, statistics, mathematics or a related field (preferred)
Minimum 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.
Data mining through state-of-the-art methods.
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. as well as a firm grip over modern state-of-the-art and good-to-have NLP architectures such as BERT, GPT3/GPT4, Reformer, RNNs, CNNs, LSTMs, etc. and vector space models such as GloVe, Word2vec, USE, etc.
Good to have Familiarity with Model Serving APIs like, Django, Flask & StreamLit. Peer-reviewed publications in topics of advanced data science, machine learning, deep learning, or NLP.
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.
Expert knowledge and Experience in working on conventional NLP problems like Informational Retrieval, Relevance Ranking, and Search, Question-Answer Generation, Natural Language Inference, Topic Modeling, Unstructured Text Pipelines/Modeling, Anomaly Detection, Text Summarization, etc.
Experience using statistical computer languages (Python, SQL, etc.) to manipulate data and draw insights from large data sets.
A drive to learn and master new technologies and techniques. Certifications in the relevant domain and demonstratable experience in research and development are a plus.
Good to have peer-reviewed publications on topics of advanced data science, machine learning, deep learning, or NLP
Competitive salary
Fuel Card
Health benefits
Professional development opportunities
Inclusive work culture & much more
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