Associate Data Scientist - AI/ML

About the job

We are looking forward to hire AI/ML Professionals in the following areas : Experience 1-3 Years Job Description • Perform as an individual contributor with high degree of accountability with minimum assistance • Presents data impactfully with the help of visualization tools • Discover trends and patterns using Data Science Tools. • Work in python/R to develop core ML solutions with data congestion, data pre-processing, data cleaning, feature engineering, feature selection, Model development and model tuning Required Technical/ Functional Competencies Domain/ Industry Knowledge: • Basic knowledge of customer's business processes and relevant technology platform or product • Able to prepare process maps, workflows, business cases and simple business models in line with customer requirements with assistance from SME and apply industry standards/ practices in implementation with guidance from experienced team members. Requirement Gathering And Analysis: • Basic knowledge of requirement management processes and requirement analysis process, tools and methodologies. • Able to prototype/ design a prototype of an example system to be demonstrated to stakeholders and extract functional/ non-functional requirements from business requirements and document a system/ software requirements specification for low to medium complexity scenarios. Product/Technology Knowledge: • Working knowledge of technology product/platform standards and specifications. • Able to implement code or configure/customize products and provide inputs in design and architecture adhering to industry standards/ practices in implementation. • Analyse various frameworks/tools, review the code and provide feedback on improvement opportunities. Analytics Solution Design: • High-level awareness of a wide range of core data science/analytics techniques, their advantages, disadvantages, and areas of application. • Able to identify the causes of errors and their potential solutions with some support. Tools & Platform Knowledge: • Familiar with wide range of mainstream commercial & open-source data science/analytics software tools, their constraints, advantages, disadvantages, and areas of application. Mathematical & Statistical Analysis: • Understanding basic mathematical concepts (e.g., algebra, calculus) and introductory statistical concepts (mean, median, standard deviation). • Able to perform basic mathematical calculations and conduct simple statistical analyses with guidance. Data Visualization: • Basic understanding of common visualization types (e.g., bar charts, line charts). • Can create simple visualizations using basic tools (e.g., Excel, basic charting libraries). Data Modeling & Evaluation: • Basic understanding of data modelling concepts. • Familiarity with basic statistical measures and evaluation metrics. • Can create simple data models with guidance. • Can use basic evaluation metrics to assess model performance. Feature Engineering: • Basic understanding of data types and structures. • Familiarity with common programming languages (e.g., Python, R). • Awareness of basic statistical concepts. • Ability to manipulate data using libraries like Pandas or NumPy. • Execute simple feature transformations, such as scaling and normalization. • Basic awareness of the importance of feature selection. Required Behavioral Competencies Accountability: • Takes ownership for and ensures accuracy of own work, meets deadlines, and asks questions about possible gaps to ensure clarity of ownership. Agility: • Demonstrates a willingness to accept and embrace differing ideas or perceptions which are beneficial to the organization. Collaboration: • Participates in team activities and reaches out to others in team to achieve common goals. Customer Focus: • Displays awareness of customers stated needs and gives priority to meeting and exceeding customer expectations at or above expected quality within stipulated time. Communication: • Effectively communicates in written and oral form, well-organized thoughts to others. Speaks openly and honestly with all employees. Drives Results: • Demonstrates a "can do" attitude and is willing to stretch self to achieve and exceed defined goals/targets. Certifications Good To Have AZ-900: Microsoft Azure Fundamentals, AWS Certified Cloud Practitioner, ITIL V4 Foundation, GCP Associate At YASH, you are empowered to create a career that will take you to where you want to go while working in an inclusive team environment. We leverage career-oriented skilling models and optimize our collective intelligence aided with technology for continuous learning, unlearning, and relearning at a rapid pace and scale. Our Hyperlearning workplace is grounded upon four principles • Flexible work arrangements, Free spirit, and emotional positivity • Agile self-determination, trust, transparency, and open collaboration • All Support needed for the realization of business goals, • Stable employment with a great atmosphere and ethical corporate culture