JOB DESCRIPTION – SENIOR ANALYST – DATA SCIENTIST

Key Responsibilities

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

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

·       Solid understanding of time-series forecasting techniques

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

·       Able to write clean and tested code that can be maintained by other software engineers

·       Able to clearly summarize and communicate data analysis assumptions and results

·       Able to craft effective data pipelines to transform your analyses from offline to production systems

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

·       Connects both externally and internally to understand industry trends, technology advances and outstanding processes or solutions

·       Is collaborative and engages (strategic & tactical. Able to influence without authority, handle complex issues and implement positive change

·       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

·       Provide guidance and leadership to more junior data scientists, managing processes and flow of work, vetting designs, and mentoring team members to realize their full potential

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

·       Provide 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

What We Are Looking For

Required Qualifications

·       Master's degree in a quantitative field such as Data Science, Statistics, Applied Mathematics or Bachelor's degree in engineering, computer science, or related field.

·       4 – 6 years of total work experience as data scientist or analytical role, with at least 2-3 years of experience in time series forecasting

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

·       Strong experience in Time Series Forecasting and Demand Planning

·       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, documentation

·       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

·       Ability to lead, manage, build, and deliver customer business results through data scientists or 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

·       Outstanding verbal and written communication skills with the ability to effectively advocate technical solutions to engineering and business teams

Desired Qualifications

·       Experience working in one or multiple supply chain functions (e.g., procurement, planning, manufacturing, quality, logistics) is strongly preferred

·       Experience in applying AI/ML within a CPG or Healthcare business environment is strongly preferred

·       Experience in creating CI/CD pipelines for deployment using Jenkins.

·       Experience implementing MLOPs framework along with understanding of data security

·       Implementation on ML models

·       Exposure to visualization packages and Azure tech stack.