Senior Data Scientist

About the Role

Key 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 involving a single function.
• Support efforts to ensure that analytical models and techniques used can be deployed into production.
• Support evaluation of the analytical model and support the scalability and sustainability of analytical models.
• Write code to develop the required solution and application features using the recommended programming language.
• Test the code using the recommended testing approach.
• Identify the model evaluation metrics and apply best practice techniques for model testing and tuning.
• Generate graphical representations of data and model outcomes.
• Design appropriate data representations for multiple data sets based on customer requirements.
• Present data insights to and influence team and business audiences using data visualization frameworks.
• Guide and mentor junior associates on story types, structures, and techniques.
• Provide recommendations to solve complex business issues and develop business cases for projects.
• Translate business requirements into projects and activities aligned with overall business strategy.
• Identify relevant business insights and connect business needs with data or mathematical solutions.
• Select suitable analytical modeling techniques and develop custom models.
• Conduct exploratory data analysis, feature engineering, and hypothesis testing.
• Define and finalize features, conduct experiments, and analyze trends and clusters.
• Mentor junior associates on basic modeling and analytics techniques.
• Support the implementation of business solutions by building relationships with stakeholders and monitoring progress.

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.
• Experience with coding in Object-oriented programming languages (Python, C++, and Java).
• Experience designing and testing Relational Database Management Systems (MySQL and Postgres).
• Implementing data science solutions using Cloud Computing environments (GCP, AWS, Azure Databricks).
• Performing statistical analysis using R.
• Visualizing data using Python, Tableau, Power BI, Matplotlib, Seaborn, and Plotly.
• Implementing supervised machine learning techniques (linear regression, logistic regression, decision trees, random forests, support vector machines, XGBoost) using Python.
• Performing statistical analysis techniques like hypothesis testing, A/B testing, t-tests, and chi-squared tests.
• Manipulating and modeling data using PySpark.
• Conducting exploratory data analysis, feature engineering, feature extraction, and feature selection using Python and R.
• Knowledge of cloud data warehousing techniques like Snowflake and BigQuery.
• Experience with ML and Deep Learning frameworks (Scikit-learn, TensorFlow, PyTorch, Keras).
• Implementing NLP techniques (tokenization, lemmatization, NER) and LLMs using Python.
• Employer will accept any amount of experience with the required skills.

Nice to Have

• Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics.
• Successful completion of assessments in Python, Spark, Scala, or R.
• Supervisory experience.
• Experience with open source frameworks (scikit-learn, TensorFlow, Torch).
• Background in creating inclusive digital experiences and implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards.
• Knowledge of accessibility best practices, assistive technologies, and integrating digital accessibility.

Qualifications

• Option 1: Bachelor's degree in relevant fields plus 5 years' experience in analytics.
• Option 2: Master's degree in relevant fields plus 3 years' experience in analytics.
• Option 3: 7 years' experience in analytics or related field.

Benefits & Perks

• Competitive pay with performance-based bonus awards.
• Health benefits including medical, vision, and dental coverage.
• Financial benefits such as 401(k), stock purchase, and company-paid life insurance.
• Paid time off benefits including PTO, sick leave, parental leave, family care leave, bereavement, jury duty, and voting.
• Other benefits like short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement.
• PTO and PPTO that can be used for vacation, sick leave, holidays, or other purposes, meeting or exceeding legal requirements.
• Live Better U education benefit program covering tuition, books, and fees for associates.