Specialty/Competency: Data, Analytics & AI

Industry/Sector: EUR X-Sector

Time Type: Full time

Travel Requirements: Up to 80%

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems.

Driven by curiosity, you are a reliable, contributing member of a team. In our fast-paced environment, you are expected to adapt to working with a variety of clients and team members, each presenting varying challenges and scope. Every experience is an opportunity to learn and grow. You are expected to take ownership and consistently deliver quality work that drives value for our clients and success as a team. As you navigate through the Firm, you build a brand for yourself, opening doors to more opportunities.

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

Apply a learning mindset and take ownership for your own development.

Appreciate diverse perspectives, needs, and feelings of others.

Adopt habits to sustain high performance and develop your potential.

Actively listen, ask questions to check understanding, and clearly express ideas.

Seek, reflect, act on, and give feedback.

Gather information from a range of sources to analyse facts and discern patterns.

Commit to understanding how the business works and building commercial awareness.

Learn and apply professional and technical standards (e.g. refer to specific PwC tax and audit guidance), uphold the Firm's code of conduct and independence requirements.

Job Requirements and Preferences

Basic Qualifications

Minimum Degree Required

Bachelor's Degree

Required Field(s) of Study

Management Information Systems,Management Information Systems & Accounting,Management of Technology,Systems Engineering,Mathematical Statistics,Mathematics,Electrical Engineering,Industrial Engineering,Computer and Information Science & Accounting

Minimum Year(s) of Experience

1 year(s)

Preferred Qualifications

Preferred Knowledge/Skills

Demonstrates thorough-level abilities and/or a proven record of success managing the identification and addressing of client needs:

Building of GenAI and AI solutions, including but not limited to analytical model development and implementation, prompt engineering, general all-purpose programming (e.g., Python), testing, communication of results, front end and back-end integration, and iterative development with clients

Documenting and analyzing business processes for AI and Generative AI opportunities, including gathering of requirements, creation of initial hypotheses, and development of GenAI and AI solution approach

Collaborating with client team to understand their business problem and select the appropriate analytical models and approaches for AI and GenAI use cases

Designing and solutioning AI/GenAI architectures for clients, specifically for plugin-based solutions (i.e., ChatClient application with plugins) and custom AI/GenAI application builds

Processing unstructured and structured data to be consumed as context for LLMs, including but not limited to embedding of large text corpus, generative development of SQL queries, building connectors to structured databases

Support management of daily operations of a global data and analytics team on client engagements, review developed models, provide feedback and assist in analysis;

Directing data engineers and other data scientists to deliver efficient solutions to meet client requirements;

Leading and contributing to development of proof of concepts, pilots, and production use cases for clients while working in cross-functional teams;

Structuring, write, communicate and facilitate client presentations; and,

Directing associates through coaching, providing feedback, and guiding work performance.

Demonstrates thorough abilities and/or a proven record of success learning and performing in functional and technical capacities, including the following areas:

Managing AI/GenAI application development teams including back-end and front-end integrations

Using Python (e.g., Pandas, NLTK, Scikit-learn, Keras etc.), common LLM development frameworks (e.g., Langchain, Semantic Kernel), Relational storage (SQL), Non-relational storage (NoSQL);

Experience in analytical techniques such as Machine Learning, Deep Learning and Optimization

Vectorization and embedding, prompt engineering, RAG (retrieval, augmented, generation) workflow dev

Understanding or hands on experience with Azure, AWS, and / or Google Cloud platforms

Experience with Git Version Control, Unit/Integration/End-to-End Testing, CI/CD, release management, etc.

Learn more about how we work: https://pwc.to/how-we-work

PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.

All qualified applicants will receive consideration for employment at PwC without regard to race; creed; color; religion; national origin; sex; age; disability; sexual orientation; gender identity or expression; genetic predisposition or carrier status; veteran, marital, or citizenship status; or any other status protected by law. PwC is proud to be an affirmative action and equal opportunity employer.

For positions based in San Francisco, consideration of qualified candidates with arrest and conviction records will be in a manner consistent with the San Francisco Fair Chance Ordinance.

Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines

The salary range for this position is: $75,000 - $118,000, plus individuals may be eligible for an annual discretionary bonus. For roles that are based in Maryland, this is the listed salary range for this position. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance

#LI-Hybrid

Job DescriptionAbout LocallyLocally is at the forefront of bridging the gap between online shopping and local retail experiences. Founded in 2013, we've built the world's largest network of specialty brands and retailers, revolutionizing the way people shop. Our mission is to fortify local economies by enabling shoppers to buy products from neighborhood retailers. Partnering with prominent names like Yeti, Trek, Sonos, Dicks, REI, Crocs, and BrooksRunning, we've created a significant impact. Our tools captivate over 30 million unique shoppers monthly, generating over 2 billion annual engagements worldwide.About the PositionWe are seeking a highly skilled and experienced Lead Data Scientist to join our dynamic team. This is a fully remote position based in the U.S. or Canada.The ideal candidate will have a deep understanding of retail & eCommerce, with a keen eye for metrics that drive brand success. You will play a pivotal role in analyzing complex data sets and building tools that extract meaningful insights, inform business decisions, and contribute to the strategic direction of Locally and our customers.ResponsibilitiesOwn the development of our data science and analytics infrastructure, tools, and best practices.Analyze large, complex data sets to uncover hidden patterns, market trends, and customer preferences.Develop and maintain customer-facing data and analytics visualization tools.Develop predictive models and machine-learning algorithms to forecast sales and assist with marketing needs.Collaborate with cross-functional teams to translate data insights into actionable business strategies via internal dashboards and memos.Present findings and recommendations to stakeholders in a clear, concise manner.Continuously monitor and assess the effectiveness of data-driven initiatives.Stay abreast of industry trends and advancements in data science and retail analytics.QualificationsProven experience in data science in the retail or e-commerce sector.Advanced degree in Data Science, Statistics, Computer Science, or a related field is preferred, but not required.Demonstrated expertise in developing, implementing, and maintaining scalable data models.Strong proficiency in statistical analysis, machine learning, and predictive modeling techniques.Advanced expertise in SQL, including writing and optimizing complex queries, database design, performance tuning, and handling large-scale datasets.Expertise in Python for data analysis, statistical modeling, machine learning, and process automation.Hands-on experience using Metabase for data visualization and insights delivery.Experience working with Google Cloud Platform (GCP) and leveraging its tools for data management and analysis.Demonstrated proficiency with data tools like BigQuery, Cloud Composer, and Apache Airflow for data processing, orchestration, and workflow automation.Excellent communication and collaboration skills, with the ability to convey technical concepts to both technical and non-technical audiences.Perks and CompensationAt Locally, we foster a casual yet rewarding work environment that prioritizes mission-driven, high-growth opportunities. Our team benefits from:A competitive salary complemented by a Bonus and Stock Option Plan.Comprehensive benefits including Medical, Dental, and Retirement Plan.Flexible remote work (100% remote team, with a strong presence on Slack).Thank you for considering this opportunity. Funded.club Senior Recruiters work exclusively with Startups and are in direct communication with hiring managers and founding team members.Your application will be fully reviewed by a dedicated recruiter who will respond based on the matching of your experience and qualifications.#J-18808-Ljbffr

Cox Communications is looking for a Lead Data Scientist to join the Data Science team supporting Cox Business. This role will be responsible for designing and implementing advanced analytics along with managing third-party data scientists. PRIMARY RESPONSIBILITIES AND ESSENTIAL FUNCTIONS: <ul><li>Design, implement, test, prototype, and deploy ML (machine learning), DL (deep learning), AI (artificial intelligence), and NLP (natural language processing) applications to extract value from Cox Communications structured and unstructured data assets. </li><li>Develop and maintain robust data pipelines to support ML/AI workflows, including data ingestion, preprocessing, transformation, and feature engineering from various data sources. </li><li>Perform end-to-end statistical analyses, from problem definition through data extraction, transformation, and insight generation. </li><li>Conduct ad-hoc analyses to meet specific and emerging business needs. </li><li>Collaborate with team members to address complex, previously unresolved challenges and improve data flow and processing efficiency. </li><li>Leverage insights and experience from past projects to support decision making and challenge assumptions from diverse perspectives. </li><li>Assist with or lead development of industry whitepapers and other technical publications. </li><li>Guide junior team members in Data Science and support contractors and third-party data scientists during the ML modeling process. </li><li>Identify and implement opportunities for automation in data processing, feature extraction, and ML workflows to drive knowledge discovery, decision making, insights, optimization, and new capabilities. </li><li>Develop frameworks and apply best practices to mature analytics and data engineering solutions from proof of concept to production. </li><li>Prepare documentation, reports, and visualizations to communicate findings effectively and ensure knowledge transfer. </li><li>Continuously evaluate and integrate new technologies, tools, and data sources to enhance data infrastructure, storage, and processing capabilities. </li> </ul> QUALIFICATIONS AND EXPERIENCE: <ul><li>Bachelor's degree in Data Science, Machine Learning, Statistics, Mathematics, Computer Science, Operations Research, Analytics or a related discipline, and 6 years' experience in a related field. The right candidate could also have a different combination, such as a master's degree and 4 years' experience; a Ph.D. and 1 year of experience; or 18 years' experience in a related field. </li><li>5+ years of experience in advanced analytics roles, including ML, AI, NLP, research, predictive analytics, and similar areas. </li><li>Strong programming skills (5+ years of experience) and proficiency in various data/analytic software, languages, and tools, including Spark (Spark SQL), R (caret, ggplot2), Python (pandas, numpy, scipy, scikitlearn, VennAbers, Mapie), Scala, Java, C++, Hive, SQL, Tableau, and others. </li><li>Expertise in machine learning and deep learning frameworks such as TensorFlow, Keras, Caffe, MXNet, and Pytorch, with a focus on developing complex programs, custom algorithms, and optimized model performance. </li><li>Extensive practical knowledge in: Cloud computing; Jira; GitHub; and production processes in cloud. </li><li>Experience developing, implementing, maintaining ML/AI solutions, and managing end-to-end data pipelines using cloud-native tools in AWS, with specific expertise in SageMaker for model training and deployment, Athena for querying large datasets, S3 for data storage and management, and EMR for big data distributed processing. </li><li>Experience in designing end-to-end ML pipelines, including data ingestion, ETL, feature engineering, and model deployment. </li><li>Experience with Hadoop and big data clusters for high volume data handling, transformation, and ETL optimization. </li><li>Experience in implementing MLOps practices to ensure efficient model deployment, monitoring, and lifecycle management, facilitating collaboration between data science and operational teams. </li><li>Deep understanding of the mathematical and computational concepts behind advanced analytics algorithms. </li><li>Strong communication skills, with the ability to translate complex analytics into actionable business insights and communicate effectively within diverse teams. </li><li>A curious mindset focused on innovation and continuous learning to drive data and analytics improvements. </li> </ul> Preferred: <ul><li>5+ years of programming experience in Python, PySpark, and SQL for scalable data processing, with expertise in building and optimizing data pipelines from raw data ingestion through model deployment. </li><li>Practical experience in Generative AI techniques (e.g., large language models, GANs) applied to transaction reduction, customer experience, and predictive analytics. </li><li>Experience in data visualization using tools like Tableau, Power BI, or Plotly to convert data into actionable insights, supporting industry specific applications in telecommunications, cable, high tech, and consulting sectors. </li> </ul> Compensation: Compensation includes a base salary of $117,300.00 - $195,500.00. The base salary may vary within the anticipated base pay range based on factors such as the ultimate location of the position and the selected candidate's knowledge, skills, and abilities. Position may be eligible for additional compensation that may include an incentive program. Benefits: The Company offers eligible employees the flexibility to take as much vacation with pay as they deem consistent with their duties, the company's needs, and its obligations; seven paid holidays throughout the calendar year; and up to 160 hours of paid wellness annually for their own wellness or that of family members. Employees are also eligible for additional paid time off in the form of bereavement leave, time off to vote, jury duty leave, volunteer time off, military leave, parental leave, and COVID-19 vaccination leave. About Cox Communications: Cox Communications is the largest private telecom company in America, serving six million homes and businesses. That's a lot, but we also proudly serve our employees. Our benefits and our award-winning culture are just two of the things that make Cox a coveted place to work. If you're interested in bringing people closer through broadband, smart home tech and more, join Cox Communications today! About Cox: Cox empowers employees to build a better future and has been doing so for over 120 years. With exciting investments and innovations across transportation, communications, cleantech and healthcare, our family of businesses - which includes Cox Automotive and Cox Communications - is forging a better future for us all. Ready to make your mark? Join us today!#J-18808-Ljbffr

Job DescriptionExecRecruitment is a global professional services provider and contingency staffing company. Our main objective is to source top talent and support professional growth.One of our direct clients is actively seeking a Data Scientist to join their team.<h3>Job Title: Data Scientist</h3>Location: Remote Duration: 6 months+ extension<h3>Duties:</h3>The duties of a Data Scientist include, but are not limited to:<ol><li>Collect, clean, and preprocess data from various sources;</li><li>Develop and implement predictive models using statistical and machine learning techniques;</li><li>Analyze and interpret complex data sets to provide insights and support decision-making;</li><li>Create visualizations to communicate results to stakeholders;</li><li>Collaborate with business stakeholders, IT teams, and other departments to define and prioritize data science projects;</li><li>Keep up-to-date with new data science technologies and industry trends to identify opportunities for innovation and improvement;</li><li>Communicate with stakeholders and provide regular updates on project progress and status.</li></ol>
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