Senior Data Science Strategist

We are seeking a highly skilled data science professional to lead our organization's data science initiatives. The successful candidate will be responsible for defining and championing the company's data science vision and strategy, aligning it with business objectives.

• Strategic Leadership: Define and prioritize high-impact data science projects that directly impact the business.
• Architecture Design: Design and architect scalable and robust data platforms and solutions to support advanced analytics and AI/ML initiatives.
• Model Development & Innovation: Lead the development and implementation of advanced statistical and machine learning models to solve complex business problems.
• Data Exploration & Analysis: Lead data exploration and analysis efforts, identifying key insights and trends that can inform business decisions.
• Mentorship & Team Leadership: Mentor and guide junior data scientists and engineers, fostering a culture of learning and growth.
• Cross-functional Collaboration: Collaborate closely with product managers, engineers, and business stakeholders to understand their needs and translate them into data-driven solutions.
• Research & Development: Stay up-to-date with the latest advancements in data science, AI/ML, and related fields.
• Thought Leadership: Represent the company at industry conferences, publish research papers, and contribute to the data science community.

Qualifications:

• Education: A Ph.D./Bachelor/Master's degree in Computer Science, Statistics, Mathematics, or a related field with a strong focus on data science and machine learning.
• Experience: 12+ years of overall experience with minimum 8+ years in data science, with a proven track record of developing and deploying successful AI/ML solutions.
• Technical Skills:
• Strong expertise in statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, deep learning), and data mining techniques.
• Proficiency in programming languages such as Python, R, or similar.
• Experience with big data technologies (e.g., Hadoop, Spark) and cloud computing platforms (e.g., AWS, Azure, GCP).
• Excellent skills in finding the central tendency (mean, median, mode), variability (range, variance, standard deviation), distribution (frequency distributions, box plots etc.). Concepts of Probability, Discrete and Continuous distributions. Discrete Distribution (Binomial, Poisson, Geometric), Continuous Distribution (Normal, Uniform, Exponential). Excellent skills in Hypothesis Testing using Z Test, finding confidence intervals for estimating population parameters, regression analysis to model the relationship between variables, correlation techniques, density estimates for estimating probability density function, chi square test for testing independence between two categorical variables, Analysis of variance (ANOVA) technique for comparing means of two groups, A/B Testing. Linear Algebra, Gradient Calculus. N Gram analysis of texts, trend analysis of text inputs etc.
• Familiarity with data visualization tools & libraries (e.g., Tableau, Power BI, Plotly, Matplotlib, Seaborn, Vega-Lite and others).
• Experience with MLOps tools and practices is a plus.
• Dimensionality reduction and feature extraction techniques like Principal Component Analysis, Singular Value Decomposition, and Linear Discriminate Analysis.
• Excellent knowledge of Generative AI (Transformer Models and Generative Adversarial Networks).

Business Acumen: Strong understanding of business principles and the ability to translate business needs into data-driven solutions.

Communication Skills: Excellent communication and presentation skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.