Job Description

• Processing, cleansing, and verifying the integrity of data used for analysis.
• Doing ad-hoc analysis and presenting results in a clear manner.
• Analyze large, complex datasets to extract insights and decide on the appropriate technique.
• Selecting features, building, and optimizing classifiers using machine learning techniques.
• Collaborate with stakeholders to understand their requirements, translate them into data-driven solutions, and communicate findings and recommendations effectively.
• Data mining using state-of-the-art methods.
• Extending customers data with third party sources of information when needed.
• Enhancing data collection procedures to include information that is relevant for building analytic systems.
• Use data modelling and evaluation strategy to find patterns and predict future trends, enabling proactive decision-making.

• Experience with data visualization tools (e.g., Tableau, Power BI, D3.js) and ability to communicate complex data insights effectively.
• Demonstrated effective interpersonal, influencing, collaboration and listening skills.
• Ability to articulate an idea with strong communication and presentation skills.
• Work as part of a small team, sharing ideas and contributing to the strategic goals.
• Experience in business service, manufacturing industry is a plus.

• Collaborate with business stakeholders and support reporting needs. This will involve using SQL, Python, Excel, and various reporting tools.
• Partner with the IT team to assist in the implementation of new datalake.
• Support data science initiatives by developing the necessary tools to meet project requirements.

• Minimum of bachelor's degree in Data Analytics, Data Science, Computer Science or any other related field of science.
• 3-7 years of professional experience as a Data Scientist or in a similar role, working with large data sets and complex analytical problems.
• Strong problem-solving critical thinking, and analytical skills with an emphasis on product development.
• Experience querying databases and using statistical computer languages.
• Experience using statistical computer languages to manipulate data and draw insights from large data sets.
• Experience with a variety of machine learning techniques and their real-world advantages/drawbacks.
• Detailed knowledge of machine learning evaluation metrics and best practice.
• Strong Python, R, SQL skills and problem-solving, good analytical & communication skills.
• Experience of working in an Agile environment for applied research.
• Knowledge of machine learning engineering end-to-end delivery process.
• Programming Languages: Python, R, SQL(Advanced)
• Statistics and Probability: Understanding of statistical methods and probability theory
• Data Wrangling: Skills in cleaning and organizing data
• Machine Learning: Experience with scikit-learn, TensorFlow, Keras or similar
• Data Visualization: PowerBI or Tableau ( Good to Have)
• Tools: Excel
• Business Acumen: Ability to translate business problems into data science solutions
• NLP and Deep learning Techniques

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