Data Scientist
Primary Skills
Problem Formulation (Business problem to Data Science Problem), OKR Validation against statistical measures, Data Wrangling, Data Storytelling & Insight Generation, Problem Solving, Excel VBA, Data Curiosity, Technical Decision Making (How many iterations to go for vs when to stop iterating), Communication & Articulation: Vocal & Written, Business Acumen (Consume new domains quickly to learn through data), Design Thinking, Data Literacy
Specialization
Data Science Foundation: AI/ML Engineer
Job requirements
Experience Range: 4 - 6 years of experience in data science, with demonstrated expertise in formulating business problems into data science solutions Key Responsibilities: 1. Formulate complex business challenges into actionable data science problems and design tailored analytical solutions 2. Validate objectives and key results (OKRs) using robust statistical measures and ensure alignment with business goals 3. Conduct comprehensive data wrangling, cleansing, and transformation to prepare datasets for modeling and analysis 4. Generate actionable insights and compelling data stories through advanced exploratory analysis and visualization techniques 5. Apply Excel VBA for automation, data manipulation, and custom reporting to streamline analytical workflows 6. Make informed technical decisions on model iterations, balancing performance improvements with resource constraints 7. Collaborate with cross-functional teams to rapidly acquire domain knowledge and drive data-driven decision making 8. Communicate findings clearly through vocal and written channels, articulating technical concepts to business stakeholders Required Skills: 1. Expertise in problem formulation from business requirements to data science solutions 2. Advanced proficiency in statistical validation of OKRs 3. Strong data wrangling and preprocessing skills using Python or R 4. Data storytelling and insight generation through visualization tools such as Tableau or Power BI 5. Excel VBA for automation and advanced data manipulation 6. Technical decision making in iterative model development 7. Data literacy across multiple domains 8. Design thinking in analytical solution development 9. Experience with machine learning model development and evaluation 10. Ability to quickly consume and analyze new domain data Preferred Skills: 1. Experience with cloud-based analytics platforms (e.g., AWS, Azure, GCP) 2. Knowledge of advanced statistical modeling techniques 3. Familiarity with big data frameworks such as Spark or Hadoop 4. Expertise in deploying data science solutions to production environments 5. Proficiency in advanced data visualization libraries (e.g., D3.js, Plotly) Desired Qualifications: 1. Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field 2. Relevant certifications in data science or analytics (e.g., Microsoft Certified Data Scientist, Google Professional Data Engineer)