Data Scientist
Job Description
Job Purpose
A data scientist turns raw data into valuable insights that an organization needs in order to grow and compete. He/she interprets and analyze data from multiple sources to come up with imaginative solutions to problems.
- Identify valuable data sources and automate collection processes
- Undertake preprocessing of structured and unstructured data
- Analyze large amounts of information to discover trends and patterns
- Build predictive models and machine-learning algorithms
- Combine models through ensemble modeling
- Present information using data visualization techniques
- Propose solutions and strategies to business challenges
- Collaborate with engineering and product teams
Key Skills
- Knowledge of R, SQL and Python; familiarity with Scala, Java or C++
- Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
- Understanding of machine-learning and operations research
- Analytical mind and business acumen paired with problem-solving ability
- Excellent communication and presentation skills.
Experience: 4-11 years
More Info
About Company
Skills:
Matplotlib, Tableau, Sql, Tensorflow, Nosql, Numpy, Nltk, Pandas, Pytorch, Seaborn, Keras, Python, Gensim, GPT, Scikit-Learn, R, BERT, SpaCy
Skills:
data engineering , Machine Learning, Data Modelling, Neural Networks, Apache Spark, Sql, Tensorflow, Business Intelligence Tools, Pytorch, XGBoost, Python, scikit-learn, Distributed cloud data frameworks, R, Julia, Statistics, real-time data processing
Skills:
Machine Learning, Predictive Modelling, Python, Sql, Contextual Bandits, NBO NBA Propensity Modelling, Customer Segmentation, GenAI Prototype Application Development
Skills:
Sql, Python, Campaign Analytics, GenAI, Customer Segmentation, customer analytics
Skills:
Clustering, Sql, MLops, Python, Computer Vision, Neural Networks, Generative AI, Statistics, Regression, versioning, Classification, Vector stores, Vision-language models, Embeddings, Experiment tracking, Prompt design and evaluation, Containerisation, Feature engineering, Model registry