Visionary Data Strategist

We are seeking a visionary leader to define and champion our data strategy, aligning it with business objectives. This role will be instrumental in driving innovation in AI/ML and building scalable data solutions that directly impact our business.

The successful candidate will be a technical leader, mentor, and thought leader, working closely with cross-functional teams to identify opportunities, develop cutting-edge models, and architect robust data platforms.

Key Responsibilities:

• Strategic Leadership: Define the company's data science vision and strategy, prioritizing high-impact data science projects and ensuring seamless alignment with business goals.
• Architecture Design: Design and architect scalable and robust data platforms and solutions to support advanced analytics and AI/ML initiatives, evaluating and selecting appropriate technologies and tools.
• Model Development & Innovation: Lead the development and implementation of advanced statistical and machine learning models to solve complex business problems, fostering a culture of innovation and experimentation.
• Data Exploration & Analysis: Lead data exploration and analysis efforts, identifying key insights and trends that inform business decisions, developing data visualizations and dashboards to communicate findings effectively.
• Mentorship & Team Leadership: Mentor and guide junior data scientists and engineers, promoting a culture of learning and growth, providing technical leadership and direction on data science projects.
• Cross-functional Collaboration: Collaborate closely with product managers, engineers, and business stakeholders to understand their needs and translate them into data-driven solutions, communicating complex technical concepts to non-technical audiences.
• Research & Development: Stay up-to-date with the latest advancements in data science, AI/ML, and related fields, contributing to research and development efforts, exploring new methodologies and technologies.
• Data Governance & Quality: Champion data governance and quality initiatives, ensuring data accuracy, consistency, and compliance, developing and implementing data quality checks and validation procedures.
• Thought Leadership: Represent the company at industry conferences, publish research papers, and contribute to the data science community, staying at the forefront of industry trends and developments.

Qualifications:

• Education: 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, emphasizing expertise in statistical modeling and machine learning algorithms.
• Experience: 12+ years of overall experience with minimum 8+ years in data science, demonstrating a proven track record of developing and deploying successful AI/ML solutions, preferably in a leadership or architectural role.
• Technical Skills:
• 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.), probability, discrete and continuous distributions, hypothesis testing using Z Test, confidence intervals for estimating population parameters, regression analysis, 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.
• Familiarity with data visualization tools & libraries (e.g., Tableau, Power BI, Plotly, Matplotlib, Seaborn, Vega-Lite).
• 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), including Large Language Models for Natural Language Processing and fine-tuning large language models.

Business Acumen:

Strong understanding of business principles, enabling translation of business needs into data-driven solutions, ensuring alignment with strategic objectives.

Communication Skills:

Excellent communication and presentation skills, with the ability to explain complex technical concepts to both technical and non-technical audiences, facilitating effective collaboration and stakeholder engagement.