Data Scientist - R/Python

Responsibilities :

- Work with business stakeholders and cross-functional SMEs to deeply understand business context and key business questions.

- Create Proof of concepts (POCs) / Minimum Viable Products (MVPs), then guide them through to production deployment and operationalization of projects

- Influence the machine learning strategy for Digital programs and projects.

- Make solution recommendations that appropriately balance speed to market and analytical soundness.

- Explore design options to assess efficiency and impact, and develop approaches to improve robustness and rigor.

- Develop analytical / modelling solutions using a variety of commercial and open-source tools (e. g., Python, R, TensorFlow).

- Formulate model-based solutions by combining machine learning algorithms with other techniques such as simulations.

- Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations, scenarios, and stories.

- Create algorithms to extract information from large, multiparametric data sets.

- Deploy algorithms to production to identify actionable insights from large databases.

- Compare results from various methodologies and recommend optimal techniques.

- Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations, scenarios, and stories.

- Develop and embed automated processes for predictive model validation, deployment, and implementation.

- Work on multiple pillars of AI, including cognitive engineering, conversational bots, and data science.

- Ensure that solutions exhibit high levels of performance, security, scalability, maintainability, repeatability, appropriate reusability, and reliability upon deployment

- Lead discussions at peer review and use interpersonal skills to positively influence decision-making.

- Provide thought leadership and subject matter expertise in machine learning techniques, tools, and concepts;

make impactful contributions to internal discussions on emerging practices.

- Facilitate cross-geography sharing of new ideas, learnings, and best practices.

Requirements :

- Bachelor of Science or Bachelor of Engineering at a minimum.

- 4+ years of work experience as a Data Scientist.

- A combination of business focus, strong analytical and problem-solving skills, and programming knowledge is able to quickly cycle the hypothesis through the discovery phase of a project.

- Advanced skills with statistical/programming software (e. g., R, Python) and data querying languages (e. g., SQL, Hadoop/Hive, Scala).

- Good hands-on skills in both feature engineering and hyperparameter optimization.

- Experience producing high-quality code, tests, and documentation.

- Experience with Microsoft Azure or AWS data management tools such as Azure Data Factory, data lake, Azure ML, Synapse, Databricks.

- Understanding of descriptive and exploratory statistics, predictive modelling, evaluation metrics, decision trees, machine learning algorithms, optimization & forecasting techniques, and/or deep learning methodologies.

- Proficiency in statistical concepts and ML algorithms.

- Good knowledge of Agile principles and process.

- Ability to lead, manage, build, and deliver customer business results through data scientists or a professional services team.

- Ability to share ideas in a compelling manner, to clearly summarize and communicate data analysis, assumptions, and results.

- Self-motivated and a proactive problem solver who can work independently and in teams.

- Must-Have : Agent Framework, RAG Framework, Chunking Strategies, LLMs, AI on cloud Services, Open Source Frameworks like Langchain, Llama Index, Vector Database, Token.

- Management, Knowledge Graph, Vision APIs, Prompt Engineering.

- Good to have : AI Algorithms, Deep Learning, Computer Vision, Hallucination Control Mechanism, and Responsible AI frameworks.