Senior Data Scientist

Senior Data Scientist

Requirements

• Master’s degree or the equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field plus 1 year of experience in an analytics related field; OR Bachelor’s degree or the equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field plus 3 years of experience in an analytics related field.
• Must have experience with coding in Object-oriented programming languages (Python, C++, and Java)
• Must have experience with designing and testing Relational Database Management System (MySQL and Postgres)
• Must have experience with implementing data science solutions using Cloud Computing environments (GCP, AWS, and Azure Databricks)
• Must have experience with performing statistical analysis using R
• Must have experience with visualizing data using Python, Tableau, Power BI, Matplotlib, Seaborn, and Plotly
• Must have experience with implementing supervised machine learning techniques (linear regression, logistic regression, decision trees, random forests, support vector machines, and XGBoost) using Python
• Must have experience with performing statistical analysis utilizing techniques like hypothesis testing, A/B testing, t-tests, and chi-squared tests
• Must have experience with manipulating and modelling data using PySpark
• Must have experience with conducting Exploratory data analysis, Feature Engineering, Feature Extraction and Feature selection techniques using Python and R
• Must have experience with Cloud data warehousing techniques like Snowflake and BigQuery
• Must have experience with ML and Deep learning frameworks (Scikit learn, TensorFlow, PyTorch, and Keras)
• Must have experience with implementing NLP techniques (tokenization, lemmatization, and NER) and LLMs using Python

Responsibilities

• Support the understanding of the priority order of requirements and service level agreements.
• Help identify the most suitable source for data that is fit for purpose.
• Perform initial data quality checks on extracted data.
• Understand, articulate, and apply principles of the defined strategy to routine business problems that involve a single function.
• Support efforts to ensure that analytical models and techniques used can be deployed into production.
• Support evaluation of the analytical model.
• Support the scalability and sustainability of analytical models.
• Write code to develop the required solution and application features by using the recommended programming language and leveraging business, technical, and data requirements.
• Test the code using the recommended testing approach.
• Identify the model evaluation metrics.
• Apply best practice techniques for model testing and tuning to assess accuracy, fit, validity, and robustness for multi-stage models and model ensembles.
• Generate appropriate graphical representations of data and model outcomes.
• Understand customer requirements to design appropriate data representation for multiple data sets.
• Present to and influence the team and business audience using the appropriate data visualization frameworks and conveys clear messages through business and stakeholder understanding.
• Customize communication style based on stakeholder under guidance, and leverages rational arguments.
• Guide and mentor junior associates on story types, structures, and techniques based on context.
• Provide recommendations to business stakeholders to solve complex business issues.
• Develop business cases for projects with a projected return on investment or cost savings.
• Translate business requirements into projects, activities, and tasks and aligns to overall business strategy and develops domain specific artifact.
• Serve as an interpreter and conduit to connect business needs with tangible solutions and results.
• Identify and recommend relevant business insights pertaining to their area of work.
• Translate/co-own business problems within one’s discipline to data related or mathematical solutions.
• Identify appropriate methods/tools to be leveraged to provide a solution for the problem.
• Share use cases and gives examples to demonstrate how the method would solve the business problem.
• Select the analytical modeling technique most suitable for the structured, complex data and develops custom analytical models.
• Conduct exploratory data analysis activities (for example, basic statistical analysis, hypothesis testing, statistical inferences) on available data.
• Define and finalize features based on model responses and introduces new or revised features to enhance the analysis and outcomes.
• Identify the dimensions of the experiment, finalize the design, test hypotheses, and conduct the experiment.
• Perform trend and cluster analysis on data to answer practical business problems and provide recommendations and key insights to the business.
• Mentor and guide junior associates on basic modeling and analytics techniques to solve complex problems.
• Demonstrate up-to-date expertise and applies this to the development, execution, and improvement of action plans by providing expert advice and guidance to others in the application of information and best practices; supporting and aligning efforts to meet customer and business needs; and building commitment for perspectives and rationales.
• Provide and support the implementation of business solutions by building relationships and partnerships with key stakeholders; identifying business needs; determining and carrying out necessary processes and practices; monitoring progress and results; recognizing and capitalizing on improvement opportunities; and adapting to competing demands, organizational changes, and new responsibilities.

Preferred Qualifications

No preferred qualifications provided.