Data Scientists

The Data Scientist is expected to harness large volumes of complex data to generate actionable insights that fuel business strategy and innovation. This role requires expertise in advanced statistical methods, machine learning techniques, and data visualization to discover patterns, forecast outcomes, and support data-driven decision-making across the organization. Transforming complex datasets into solutions is a key aspect of the role, leveraging statistical expertise and machine learning to answer crucial business questions. This includes collecting, cleaning, and preprocessing structured and unstructured data from various sources such as databases, APIs, logs, and documents. Investigating data sets to identify patterns, anomalies, trends, and correlations through Exploratory Data Analysis (EDA) is essential for informing hypotheses and model development. Designing, implementing, and fine-tuning statistical and machine learning models for prediction, classification, segmentation, and recommendation tasks is a core responsibility. Evaluating model performance using appropriate metrics and iterating to improve robustness and generalizability is crucial. Translating complex model outputs into intuitive visualizations and business-relevant narratives using tools like Power BI, Tableau, or custom dashboards is important for effective data storytelling and visualization. Presenting findings and actionable recommendations to stakeholders in a clear and compelling manner to enable informed decision-making across departments is a key part of the role. Collaborating closely with business, product, engineering, and operations teams to understand domain-specific challenges and deliver tailored data-driven solutions is essential. Staying updated on the latest developments in data science, AI/ML frameworks, and big data technologies to incorporate cutting-edge methods into workflows is also a required aspect. The ideal candidate should possess deep proficiency in Python or R, along with fluency in SQL and familiarity with core data manipulation libraries such as NumPy, Pandas, and Scikit-learn. The ability to translate complex data outputs into clear, concise, and visually compelling insights for technical and non-technical stakeholders is necessary. A solid grasp of business fundamentals to connect analytical findings with strategic decision-making is crucial, along with having a naturally analytical mindset and a passion for uncovering insights, solving problems, and discovering meaningful patterns within data. Educational qualifications for this role include an advanced degree (Masters or PhD) in a quantitative discipline such as Statistics, Mathematics, Computer Science, or a closely related field. The ideal candidate should have 3+ years of demonstrated experience in data science, showcasing a strong command of statistical modeling and machine learning techniques. The Data Scientist role falls under the Software Division and reports to the CTO Org.,