Data Scientist

Job Responsibilities: 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. Qualifications 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. Projects: 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. Professional Education and Experience 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 3B Staffing LLC