SENIOR ANALYST ( DATA SCIENTIST )

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.