We are seeking a highly experienced and visionary Principal Data Scientist/Architect to lead and shape our data science initiatives. This role will be instrumental in defining our data strategy, driving innovation in AI/ML, and building scalable data solutions that directly impact our business. The role 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.
Responsibilities:
Strategic Leadership:
Define and champion the company's data science vision and strategy, aligning it with business objectives. Identify and prioritize high-impact data science projects.Architecture Design:
Design and architect scalable and robust data platforms and solutions to support advanced analytics and AI/ML initiatives. Evaluate and select appropriate technologies and tools.Model Development & Innovation:
Lead the development and implementation of advanced statistical and machine learning models to solve complex business problems. Drive innovation by exploring and experimenting with new algorithms and techniques.Data Exploration & Analysis:
Lead data exploration and analysis efforts, identifying key insights and trends that can inform business decisions. Develop data visualizations and dashboards to communicate findings effectively.Mentorship & Team Leadership:
Mentor and guide junior data scientists and engineers, fostering a culture of learning and growth. Provide 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. Communicate 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. Contribute 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. Develop and implement data quality checks and validation procedures.Thought Leadership:
Represent the company at industry conferences, publish research papers, and contribute to the data science community.
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.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. Experience in a leadership or architectural role is highly preferred.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 in Data Pre-processing which includes- Multiple Data Cleaning and Data Wrangling techniques, multiple Feature Engineering techniques of different types of data.
- Excellent in Descriptive and Inferential statistics. Excellent skills in finding the central tendency (mean, median and 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. Drawing inferences from data visualization).
- 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). At least one project in Transformer Models (Large Language Models) for Natural Language Processing. Or At-least 1 project in Transformer models or Generative Adversarial Network models for Image/Video generation or Speech Recognition.
- Has worked on multiple Transformer Models (large Language Models)
for
Natural Language Processing. Has used Fine tuning and evaluating Large Language Models. Re-Infor cement Learning and Large Language Models powered applications. Prompt Engineering using Chat GPT.
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.
