machine learning manager

Mashreq

<div>
 Job Description
 
 Designation: Assistant Manager &ndash; RBG Analytics
 
 Department: RBG Analytics
 
 Experience: 6-8 Years
 
 Location: Pakistan
 
 
 Role Purpose
 
 The Assistant Manager &ndash; AI &amp; Machine Learning will support the development of advanced analytics and AI-driven solutions to enhance digital banking performance, customer engagement, and marketing effectiveness. The role focuses on leveraging customer digital footprint data across digital channels to generate insights, develop predictive models, and optimize digital marketing campaigns and customer journeys.
 
 In addition to traditional machine learning expertise, the role requires foundational AI Engineering capabilities, including familiarity with Large Language Models (LLMs) and their application in banking use cases such as customer support automation, intelligent search, and digital engagement solutions.
 
 The role requires strong analytical capability, technical expertise in machine learning, and the ability to translate digital behavioral data into actionable insights that support business growth and customer experience initiatives.
 
 
 Ability to deliver Use cases in RM Efficiency/Productivity improvement
 
 Ability to do Analytics on Commercial Banking / Corporate Banking Portfolio and Identity Opportunities
 
 Portfolio Analytics on CASA Portfolio to support CASA Squad and Product team
 
 Bringing robust tracking and campaign fulfillment process for Liabilities /Trade Finance/ Working Capital
 
 
 Key Result Areas (KRA)
 
 1. Machine Learning &amp; Predictive Analytics
 
 - Develop and deploy machine learning models to support digital banking use cases such as customer segmentation, churn prediction, next-best-product recommendations, and campaign targeting.
 
 - Implement predictive analytics models to improve customer engagement and product adoption across digital channels.
 
 - Continuously monitor model performance and refine algorithms to improve accuracy and business impact.
 
 Digital Marketing Analytics
 
 - Support marketing teams in evaluating digital campaign performance using advanced analytics and AI-driven insights.
 
 - Build models for campaign targeting, customer propensity, and marketing attribution.
 
 - Provide insights on channel effectiveness, campaign ROI, and customer acquisition strategies.
 
 4. AI Engineering &amp; LLM Applications
 
 - Support the design and development of AI-powered solutions using Large Language Models (LLMs) for digital banking use cases.
 
 - Assist in building AI-driven tools such as chatbots, intelligent assistants, knowledge search, and automated content generation.
 
 - Integrate AI models and APIs into banking platforms and analytics workflows.
 
 - Experiment with prompt engineering and model fine-tuning to enhance AI solution performance.
 
 5. Data Preparation &amp; Feature Engineering
 
 - Extract, clean, and transform large datasets from multiple banking systems and digital platforms.
 
 - Develop feature engineering strategies to improve machine learning model performance.
 
 - Work with data engineering teams to ensure efficient data pipelines for analytics use cases.
 
 6. Collaboration with Business &amp; Product Teams
 
 - Work closely with digital banking, marketing, and product teams to identify data-driven opportunities.
 
 - Translate business requirements into analytical models and actionable insights.
 
 - Present findings and recommendations to stakeholders to support strategic decisions.
 
 
 Problem Solving &amp; Decision Making
 
 Analytical Problem Solving
 
 - Analyze complex datasets to identify patterns, anomalies, and opportunities that improve customer engagement and digital banking performance.
 
 - Apply statistical techniques and machine learning methods to solve real business challenges.
 
 AI Solution Design
 
 - Support decision-making related to the selection and application of AI/ML models, including LLM-based solutions for digital banking processes.
 
 - Evaluate trade-offs between model performance, scalability, and usability in production environments.
 
 Data Interpretation &amp; Business Insights
 
 - Translate complex analytical outputs into clear business insights that can inform marketing strategies and product development.
 
 
 Technical Skills
 
 Programming &amp; Data Analysis
 
 - Strong proficiency in Python for machine learning and data analysis.
 
 - Experience with SQL for data extraction and manipulation.
 
 - Knowledge of R is an added advantage.
 
 Machine Learning &amp; AI
 
 - Experience with machine learning algorithms including regression, classification, clustering, and recommendation systems.
 
 - Hands-on experience with libraries such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or LightGBM.
 
 AI Engineering &amp; LLM Technologies
 
 - Understanding of Large Language Models (LLMs) and their applications.
 
 - Experience working with LLM APIs and frameworks (e.g., OpenAI APIs, LangChain, or similar frameworks).
 
 - Basic knowledge of prompt engineering, embeddings, and retrieval-augmented generation (RAG).
 
 - Familiarity with developing AI-enabled applications such as chatbots or knowledge assistants.
 
 Data Processing
 
 - Experience working with large datasets using Pandas, NumPy, and big data frameworks such as PySpark or Spark.
 
 Digital Analytics Tools
 
 - Familiarity with digital analytics platforms such as Google Analytics, Adobe Analytics, or similar tools.
 
 - Experience analyzing customer digital behavior and clickstream data.
 
 Data Visualization
 
 - Ability to build dashboards and visualizations using Power BI, Tableau, or similar BI tools.
 
 
 Skills &amp; Competencies
 
 - Strong analytical and problem-solving abilities
 
 - Ability to work with large and complex datasets
 
 - Understanding of digital customer journeys and online behavior analytics
 
 - Foundational understanding of AI engineering concepts and LLM applications
 
 - Effective communication and presentation skills
 
 - Ability to translate analytical insights into business recommendations
 
 - Collaborative approach to working with cross-functional teams
 
 
 Educational Qualifications
 
 Bachelor&rsquo;s or master&rsquo;s degree in one of the following disciplines:
 
 - Computer Science
 
 - Data Science
 
 - Artificial Intelligence
 
 - Statistics
 
 - Engineering or related quantitative field Bottom of Form
</div>

Assistant Manager - Analytics (Mashreq Global Network Pakistan)

Arrow Electronics

<div>
 
 Position
 
 
 
 Data Scientist / Senior Machine Learning Engineer
 
 
 
 Job Description
 
 
 
 
 Position Overview:
 
 
 
 As Data Scientist / Senior Machine Learning Engineer at Arrow Electronics, you will assume a pivotal role in driving our data science and machine learning initiatives to reach unprecedented heights. Collaborating closely with cross-functional multinational teams, your responsibilities will encompass the end-to-end machine learning lifecycle, including stakeholder communications, data analysis, designing, development, deployment, and optimization of cutting-edge models aimed at addressing intricate challenges and generating actionable insights. Your expertise in data analysis, model development, and deployment will be crucial in shaping the future of our company.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Machine Learning Model Development: Design, develop, and implement advanced machine learning models and algorithms to solve real-world problems in various domains.
 </li>
 <li>
 Data Analysis: Explore and analyze large datasets to extract meaningful insights and identify trends, anomalies, and patterns.
 </li>
 <li>
 Model Evaluation: Evaluate the performance of machine learning models using appropriate metrics and fine-tune models for optimal results.
 </li>
 <li>
 Deployment: Lead the deployment of machine learning models into production environments and ensure scalability and efficiency.
 </li>
 <li>
 Cross-functional Collaboration: Collaborate closely with business stakeholders, software engineers, data engineers, and domain experts to integrate machine learning solutions into our products and services.
 </li>
 <li>
 Mentorship: Provide guidance and mentorship to junior data scientists and machine learning engineers, fostering a culture of continuous learning and growth.
 </li>
 <li>
 Research and Innovation: Stay up-to-date with the latest advancements in the field of data science and machine learning and apply innovative techniques to solve complex challenges.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Proven experience (2 to 5 years) in developing and deploying machine learning models in a production environment.
 </li>
 <li>
 Proficiency in programming languages, especially Python, and experience with data-related libraries such as pandas, matplotlib, NumPy, etc.
 </li>
 <li>
 Strong knowledge of machine learning frameworks and libraries.
 </li>
 <li>
 Expertise in data preprocessing, feature engineering, and model selection.
 </li>
 <li>
 Familiarity with large language models and AI agent design.
 </li>
 <li>
 Experience with text-based NLP, information extraction, entity recognition, and text-related data science tasks is highly desirable.
 </li>
 <li>
 Strong communication skills and the ability to convey technical concepts to non-technical stakeholders.
 </li>
 <li>
 Experience with vectorized databases and unstructured search engines is a plus.
 </li>
 <li>
 A Master&rsquo;s degree in computer science, Statistics, Data Science, or a related field is a plus.
 </li>
 <li>
 Publications or contributions to open-source projects are a plus.
 
 
 </li>
 </ul>
 If you are a passionate and experienced Data Scientist / Senior Machine Learning Engineer who thrives on solving challenging problems and wants to make a significant impact in the field, we encourage you to apply and join our dynamic team at Arrow Electronics Together, we will drive innovation and shape the future of data science and machine learning.
 
 
 
 Location:
 
 
 
 EG-Cairo, Egypt (Al Emdad &amp; Al Tamween)
 
 
 
 Time Type
 
 
 
 Full time
 
 
 
 Job Category
 
 
 
 Information Technology
</div>

Data Scientist / Senior Machine Learning Engineer

Select Minds LLC

<div><div><div>Benefits:</div>
<ul><li>HYBRID</li>
<li>Competitive salary</li>
<li>Opportunity for advancement</li>
</ul></div><div><div>Technical Project Manager | Data Engineering &amp; Data Science 
Location: Dallas, TX Hybrid (Onsite + Remote) 
Employment Type: Full Time / Contract (W2) 
Duration: 12+ Months (Ongoing) 
Cloud Environment: Amazon Web Services (AWS) 
Team Structure: US Onsite Teams and Offshore GCC Teams 
Compensation: Competitive Market Rate
 
 
We are seeking an experienced Technical Project Manager with strong expertise in Data Engineering and Data Science programs to lead enterprise initiatives within a large commercial airline environment. 
 
In this role, you will coordinate project delivery between onsite leadership in the United States and offshore Global Capability Center (GCC) teams, driving AWS-based Data Engineering, Analytics, and Machine Learning initiatives from planning through successful delivery. 
 
Required Qualifications 
 
Technical Skills 
<ul><li>Experience managing Data Engineering and/or Data Science projects</li><li>Strong understanding of AWS data services: Amazon S3 &bull; AWS Glue &bull; Amazon Redshift &bull; Amazon EMR &bull; Amazon Athena &bull; Amazon SageMaker &bull; AWS Lambda &bull; AWS Step Functions</li><li>Knowledge of ETL/ELT frameworks and modern data pipeline architecture</li><li>Familiarity with Machine Learning lifecycle management</li><li>Experience with Agile delivery methodologies (Scrum or SAFe)</li><li>Experience using Jira, Confluence, or similar project management tools</li><li>Understanding of cloud security, data governance, and data quality best practices</li></ul> 

Project Management 
<ul><li>Experience managing complex enterprise technology programs</li><li>Experience coordinating onsite and offshore GCC teams</li><li>Strong skills in project planning, dependency management, risk management, and stakeholder communication</li><li>Ability to communicate technical concepts effectively to executive leadership</li></ul> 

Professional Skills 
<ul><li>Excellent verbal and written communication</li><li>Strong organizational and planning abilities</li><li>Ability to manage multiple priorities in a fast-paced environment</li><li>Comfortable working with cross-functional and multicultural teams</li></ul> 

Key Responsibilities 
 
Project Delivery 
<ul><li>Lead end-to-end delivery of Data Engineering and Data Science initiatives</li><li>Define project scope, timelines, milestones, and success metrics</li><li>Manage project plans, RAID logs, risk registers, and executive status reporting</li><li>Lead Agile ceremonies including sprint planning, stand-ups, reviews, and retrospectives</li></ul> 

Offshore Team Coordination 
<ul><li>Serve as the primary liaison between onsite stakeholders and offshore GCC teams</li><li>Coordinate work across multiple time zones</li><li>Manage resource planning, priorities, escalations, and delivery governance</li><li>Ensure transparency and accountability across distributed teams</li></ul> 

Technical Leadership 
 
AWS Technologies: Amazon S3 &bull; AWS Glue &bull; Amazon Redshift &bull; Amazon EMR &bull; AWS Lambda &bull; Amazon SageMaker &bull; Amazon Athena &bull; AWS Step Functions 
 
Additional responsibilities include: 
<ul><li>Partner with Data Engineers and Data Scientists</li><li>Support architecture reviews and data pipeline planning</li><li>Coordinate Machine Learning model deployments</li><li>Ensure compliance with cloud security, data governance, and data quality standards</li></ul> 

Stakeholder Management 
<ul><li>Present project updates to executive leadership</li><li>Act as the primary point of contact for business and technology stakeholders</li><li>Identify project risks and drive mitigation plans</li><li>Facilitate collaboration across Engineering, Analytics, Operations, and IT teams</li></ul> 

Preferred Qualifications 
Certifications : PMP &bull; PMI-ACP &bull; Certified Scrum Master (CSM) &bull; SAFe &bull; AWS Cloud Practitioner &bull; AWS Solutions Architect 
Industry Experience :Commercial Airlines &bull; Travel &bull; Transportation &bull; Logistics 
Additional Technical Experience : Kafka &bull; Amazon Kinesis &bull; Tableau &bull; Amazon QuickSight &bull; Microsoft Power BI &bull; DataOps &bull; MLOps 
Domain Knowledge :Passenger Operations &bull; Revenue Management &bull; Fleet Analytics &bull; Loyalty Programs 
 
Before You Apply 
Please ensure you meet most of the following qualifications: 
<ul><li>Experience managing Data Engineering or Data Science programs</li><li>Strong understanding of AWS data services</li><li>Experience leading Agile project teams</li><li>Experience coordinating onsite and offshore teams</li><li>Strong stakeholder management and executive communication skills</li><li>Ability to work in a Hybrid environment</li><li>Valid authorization to work in the United States under one of the accepted work authorization categories</li></ul></div>
</div>
Flexible work from home options available.</div>

Technical Project Manager Data Engineering Data Science

be group

<div><div>We are assisting our client in hiring for a Senior Machine Learning Engineer.</div>
<div>Our client is an established SaaS company serving banks, credit unions, and fintechs. Their cloud-based platform helps financial institutions improve collections performance, deliver a better consumer experience, reduce operating costs, anticipate delinquencies, and make more informed credit decisions.</div>
This is a hybrid position based in Malvern, Pennsylvania. Candidates should be local to the Greater Philadelphia region and able to work onsite several days a week.
As part of a significant investment in Data &amp; AI, our client is expanding its engineering organization with two newly created Machine Learning positions. This role is focused on building the predictive intelligence that becomes part of the company's core SaaS platform.
This is a highly hands-on engineering opportunity for someone who enjoys solving real business problems with machine learning. You'll design, build, deploy, and continuously improve production models that help financial institutions better predict customer behavior, prioritize collections strategies, and improve lending outcomes.
Working alongside Product, Engineering, Data, and business leaders, you'll help transform large volumes of structured data into intelligent software capabilities that customers use every day. If you enjoy owning the entire machine learning lifecycle&mdash;from feature engineering and model development through deployment, monitoring, and optimization&mdash;this is an opportunity to make a measurable impact.
<h3 class="jobSectionHeader">What We're Looking For</h3>
<ul><li>Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical discipline.</li>
<li>3+ years of experience designing, developing, and deploying production machine learning solutions.</li>
<li>Strong Python and SQL development skills.</li>
<li>Experience building predictive models using structured data.</li>
<li>Experience with feature engineering, model evaluation, deployment, and ongoing model monitoring.</li>
<li>Experience working with cloud-based data platforms and modern machine learning frameworks.</li>
<li>Familiarity with Azure, Databricks, MLflow, MLOps, or similar technologies.</li>
<li>Experience collaborating with engineering, product, and business teams to deliver production-ready AI solutions.</li>
</ul><h3 class="jobSectionHeader">Preferred Experience</h3>
<ul><li>Financial services, banking, lending, collections, credit risk, or fintech.</li>
<li>Building scalable data pipelines and production machine learning systems.</li>
<li>AI-assisted software development tools and modern engineering practices.</li>
<li>Passion for solving complex business problems through data and machine learning.</li></ul></div>

Senior Machine Learning Engineer

JPMorganChase

<div>JOB DESCRIPTION 
 
 
At JPMorgan Chase, AI and technology promote our global operations with unmatched scale and speed. We invest over $18 billion annually in innovation, data leverage, and security to shape the future for our clients, communities, and employees. The Chief Data &amp; Analytics Office (CDAO) accelerates our data and analytics journey, with the Machine Learning Center of Excellence (MLCOE) creating and deploying solutions for complex business challenges. By ensuring data quality and leveraging insights, the CDAO supports our commercial goals, enhancing productivity and risk management through AI and machine learning. The CDAO is also responsible for developing and implementing solutions that support the firm's commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.
As a Machine Learning Scientist &ndash; Natural Language Processing (NLP) - Senior Associate, you will own the full lifecycle of developing and deploying machine learning solutions, from ideation to production. Acting as a leading voice within JPMC on all things Generative AI (GenAI), you will partner closely with all lines of business to innovate new solutions that drive transformational change for the bank. You will actively participate in our knowledge sharing community, representing your work inside and outside of the firm at leading industry conferences amongst peers and leaders in the space. We seek someone who excels in a highly collaborative, fast-paced environment, and holds a strong passion for machine learning to make a significant impact at a leading global financial institution.
Job responsibilities
<ul><li>Research and develop state-of-the-art machine learning models to solve real-world problems and apply them to tasks involving Generative AI (GenAI)
</li><li>Act as a thought partner for JPMC leaders and help the business identify and implement new machine learning methods that deliver impact
</li><li>Drive cross-functional collaboration with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy, and Business Management to deploy solutions into production
</li><li>Lead firm-wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business
</li></ul>Required qualifications, capabilities, and skills
<ul><li>PhD in a quantitative discipline, e.g., Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science, OR an MS with at least 2 years of industry or research experience in the field
</li><li>Solid background in Generative AI (GenAI) and hands-on experience and solid understanding of machine learning and deep learning methods and toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
</li><li>Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
</li><li>Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
</li><li>Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences
</li></ul>Preferred qualifications, capabilities, and skills
<ul><li>Strong background in Mathematics and Statistics; Familiarity with the financial services industries and continuous integration models and unit test development
</li><li>Knowledge in search/ranking or Meta Learning
</li><li>Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large-scale distributed environment, and ability to develop and debug production-quality code
</li><li>Published research in areas of Machine Learning or Deep Learning at a major conference or journal
</li></ul>#MLCOE_jobs
#CDAO_CAO_jobs
ABOUT US 
 
 
<div><div>JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
</div><div>We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
<div>We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase &amp; Co. is an Equal Opportunity Employer, including Disability/Veterans 
</div></div></div> 
 
ABOUT THE TEAM
 
 
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.</div>

Machine Learning Scientist - Natural Language Processing (NLP) - Senior Associate - Machine Learning Center of Excellence

Stitch Fix

<div><div><h3 class="jobSectionHeader">About Stitch Fix, Inc.
</h3>Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we're equally committed to building yours. We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what's possible for our clients, while we help you reach your full potential.</div> 

<h1 class="jobSectionHeader">
About the Role</h1>

The Client Experience Product Algorithms team is responsible for the machine learning, AI, experimentation, and product analytics capabilities that power personalized experiences for Stitch Fix clients and stylists. Partnering across Product, Engineering, Design, Styling, Marketing, Merchandising, Finance, Enterprise Analytics, Data Platform, and DSN, the team translates data and algorithms into measurable business impact.

As Director, Product Algorithms, you will lead the strategy, execution, and people behind our Growth, Styling, and Fix &amp; Freestyle Algorithms portfolios. You'll define how AI, machine learning, experimentation, and analytics shape the future of personalized shopping while building the operating discipline, technical excellence, and cross-functional alignment needed to deliver scalable business results.
<h2 class="jobSectionHeader">
Responsibilities</h2>
<ul><li>Lead the Product Algorithms portfolio across Growth, Styling, and Fix &amp; Freestyle, setting strategy and driving measurable outcomes across acquisition, engagement, retention, styling quality, Fix, Freestyle, outfitting, and related commerce experiences.</li>
<li>Define the vision and roadmap for applying data science, machine learning, AI, experimentation, and product analytics to improve client experiences, stylist effectiveness, and business performance.</li>
<li>Drive innovation by identifying, evaluating, and scaling modern AI, machine learning, personalization, and experimentation techniques that create meaningful impact while balancing technical feasibility, execution capacity, and business priorities.</li>
<li>Strengthen organizational effectiveness by improving planning, prioritization, experimentation practices, product analytics capabilities, operational readiness, incident management, and cross-functional decision making across the portfolio.</li>
<li>Build and develop a high-performing organization of managers and senior individual contributors, fostering technical excellence, strong product leadership, accountability, and collaborative partnerships while representing Product Algorithms with executive stakeholders.</li>
</ul><h2 class="jobSectionHeader">How AI and Tools Show Up in Your Day-to-Day Work</h2>
<ul><li>Use AI-powered tools (such as ChatGPT, GitHub Copilot, and other emerging technologies) to improve decision making, productivity, communication, and operational efficiency.</li>
<li>Leverage experimentation platforms, analytics tools, machine learning infrastructure, and product development systems to guide roadmap decisions and measure business impact.</li>
<li>Continuously evaluate and adopt new AI capabilities, technologies, and ways of working that improve team effectiveness and accelerate innovation.</li>
</ul><h1 class="jobSectionHeader">About You</h1>

You are a strategic technical leader who combines deep expertise in machine learning and AI with exceptional product thinking, organizational leadership, and business judgment. You thrive in highly collaborative environments, enjoy solving ambiguous problems, and know how to translate emerging technologies into measurable customer and business outcomes.
<h2 class="jobSectionHeader">
Requirements</h2>
<ul><li>Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, Mathematics, or a related quantitative field; advanced degree preferred.</li>
<li>10+ years of experience in data science, machine learning, experimentation, product analytics, AI, or algorithmic product development, including 5+ years leading teams and experience managing managers or senior technical leaders.</li>
<li>Demonstrated success defining strategy and delivering production machine learning, AI, personalization, or experimentation capabilities that drive measurable product and business outcomes.</li>
<li>Strong technical fluency across modern machine learning, generative AI/LLMs, experimentation methodologies, product analytics, and production algorithmic systems.</li>
<li>Experience building cross-functional partnerships with Product, Engineering, Design, Analytics, Data Platform, Marketing, Merchandising, Finance, and executive stakeholders.</li>
<li>Exceptional strategic thinking, communication, prioritization, problem-solving, and organizational leadership skills, with the ability to influence across technical and non-technical audiences.</li>
<li>Experience using AI tools (such as ChatGPT, GitHub Copilot, or similar technologies) to improve productivity, decision making, collaboration, and the quality of work.</li>
<li>This position requires the ability to sit for extended periods of time, use a computer and standard office equipment, and communicate effectively in both written and verbal formats.</li>
</ul><h2 class="jobSectionHeader">Nice to Have</h2>
<ul><li>Advanced degree (MS or PhD) in Computer Science, Machine Learning, Statistics, Operations Research, Engineering, or a related field.</li>
<li>Experience leading AI- or ML-driven consumer products within e-commerce, marketplaces, retail, recommendations, personalization, or digital consumer experiences.</li>
<li>Experience building or evolving experimentation platforms, product analytics capabilities, or AI governance and operational excellence practices.</li>
<li>Familiarity with large-scale recommendation systems, ranking models, generative AI applications, causal inference, optimization, or reinforcement learning.</li>
<li>Experience leading organizations through significant technical transformation, organizational scaling, or AI adoption initiatives.</li>
</ul><div>
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Director, Data Science & Algorithms - CX Product Experiences

<div>
 
 
 We're Hiring: AI &amp; Automation Analyst
 
 
 
 We are looking for an
 
 AI &amp; Automation Analyst
 
 to join our team. This is an exciting opportunity for professionals with a passion for Artificial Intelligence, Machine Learning, and Automation to contribute to innovative solutions that enhance business processes and drive digital transformation.
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Analyze business needs and identify opportunities for AI and automation.
 </li>
 <li>
 Design, develop, and implement AI solutions and automated workflows.
 </li>
 <li>
 Build and deploy machine learning models and automation scripts.
 </li>
 <li>
 Collaborate with cross-functional teams to deliver business-driven technology solutions.
 </li>
 <li>
 Prepare, analyze, and manage data to support AI initiatives.
 </li>
 <li>
 Monitor, test, and continuously improve AI and automation solutions.
 </li>
 <li>
 Ensure compliance with data privacy and security standards.
 </li>
 </ul>
 
 
 Qualifications:
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Data Science, or a related field.
 </li>
 <li>
 1&ndash;3 years of experience in AI technologies, Machine Learning, and Automation.
 </li>
 <li>
 Proficiency in Python, R, or Java.
 </li>
 <li>
 Strong analytical, problem-solving, and communication skills.
 </li>
 <li>
 Experience with automation tools and integrating AI solutions into business processes.
 </li>
 <li>
 Certifications in AI, Machine Learning, RPA, or PMP are considered an advantage.
 </li>
 <li>
 Experience within the FMCG industry is a plus.
 </li>
 </ul>
 
 
 
</div>

AI and Automation Analyst

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