Senior Machine Learning Engineer

TheSeniorMachine Learning Engineer willleveragea structured systematic approach to analyze and extract insights from massive datasets both structured and unstructured.This role requires strong expertise in relational database models including data vaulting techniques and rules tables as well as advanced proficiency in distributed computing frameworks such as Hadoop and NoSQL.A solid foundation in machine learning algorithms and familiarity with AI toolkits is essential along with knowledge of statistical methods and modeling techniques such as regression clustering principalcomponentanalysis decision trees and survival analysis. The ideal candidate combines technical depth with analytical rigor to develop scalable solutions that uncover hidden patterns and drive data-driven decision-making.

Position Responsibilities:

• Support data operations lifecycle of AA projects - Input into the approach andOwnsandmanagesassigned tasks.

• Develops and implements ad-hoc and business analytics and reporting on projects of moderate scope

• Own data pipeline and productionizing

• Identifyand gain access to sources of data with limitedassistancefrom senior team members.

• Work with internal and external team members to understand the data; present findings to the team.

• Document theacquireddata via standard team templates; present findings to the team

• Createappropriate tablesand DBs

• Work with internal and external team members to code DSs solution in production system coach junior team members.

• Acquiredata to measure effectiveness of the solution present findings to internal and external peers with guidance from senior team members.

• Works on problems of moderate scope / complexity where analysis of situations or data requires a review of a variety of factors

• Ability to generate relevant actionable insights based on iterative data analysis translate data-driven output into business language and to makeappropriate recommendationsto respective business stakeholders

• Strong ability to extract transform and stage data for consumption by the data scientistleveragingdata querying tools

• Provides analysisondatasets of significant complexity.

• Quickly able to develop enough business insight to connect data sources across multiple diverse and complicated systems.

• Communicates business analytics of moderate complexity to more senior team members and junior business partners

• Works closely with subject matter experts to understand data sources.

• Hasintimateunderstanding of the business value chain and customer lifecycle for the projects they are supporting.

• Has fundamental understanding of the business as a whole.

• Curious and asks the right kinds of questions of peers and customers to gain knowledge.

• Establishes an internal network andleveragesthe network of more senior data analysts.

• Provides guidance and mentorship to more junior team members Owns their career development.

• Takesadvantage of available resources to advance their technical and business skills.

• Understands how their project supports broader business strategy including the core drivers of business value

Required Qualifications:

• Minimum of4years of applicable experience Advanced knowledge of programming languages and concepts (g. Java Sequel C SAS SPSS R (different modules)orPython)

• Advanced knowledge of data visualization tools such as Tableau QlikView PowerBI

• Advanced knowledge of data transformation to support BI ReportingAdvancedknowledge of common database querying languages such as SQL.

• MinimumBachelorsdegree in Math Computer Science or Engineering; orBachelorsdegree with equivalent technical experience

Preferred Qualifications:

• Capability of applying a systematic structured approach to explore / navigate / mine massiveamountof data structured or un-structured to uncover hidden patterns / insights.

• Strong working knowledge of relational database models( datavaulting techniques rules tables).

• Advanced knowledge in distributed computing - Hadoop/ NoSQL/unstructured data

• Basic understanding of different techniques and knowledge of machine learning algorithms.

• Basic knowledge of AI toolkits.

• Familiarity with basic statistical tests distributions maximum likelihood estimators statistical modelling techniques (regression cluster / factor /principlecomponents decision tree survival analysis etc.)

When you join our team:

• Wellempower you to learn and grow the career you want.

• Wellrecognize and support you in a flexible environment where well-being and inclusion are more than just words.

• As part of our global teamwellsupport you in shaping the future you want to see.

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