Boston, MA

Data Jobs in Boston, MA

28 jobs found

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Today

Expert Consultant, Coro, AI Engineer

Bain & Co. Boston, MA

Boston, MA

Today

$129k - $172k/yr Full time Python Agentic Ai Artificial Intelligence

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Job Description

This role places you as an AI Engineer within Bain's Coro team, developing GenAI powered tools and data analytics to support Commercial Excellence. The focus is on LLM driven features, agentic workflows, and delivering production ready AI applications.

Responsibilities

Develop AI powered tools and products that deliver measurable business outcomes.
Design GenAI applications such as copilots, workflow automation, and decision support for commercial teams using modern large language model stacks.
Implement agentic workflows with emphasis on reliability, safety, and clear failure modes, including tool usage, multi-step execution, and human in the loop controls.
Design and build advanced search, retrieval, and knowledge pipelines across diverse data stores, covering hybrid search, vector stores, graphs/knowledge graphs, and traditional data platforms, with indexing strategies, metadata design, relevance tuning, freshness, caching, access controls, and source attribution.
Develop robust agent capabilities including context engineering, memory and state management, orchestration, routing, and tool integration patterns.
Integrate AI solutions into enterprise environments and workflows via APIs, data systems, and collaboration tools, balancing quality, latency, cost, privacy, and adoption.
Translate ambiguous client needs into clear technical requirements, tradeoffs, and delivery plans.
Build and apply data science and machine learning capabilities, delivering end to end ML solutions from data preparation and feature engineering to model selection, training, validation, testing, and performance analysis.
Apply methods spanning classical ML and deep learning, including sequence, text, and image models when relevant.
Create reproducible training and evaluation pipelines with versioning, experiment tracking, robust validation, and clear documentation.
Demonstrate fluency with modern deep learning concepts, including transformer fundamentals and LLM pre training versus post training concepts such as instruction tuning and preference optimization.
Engineer for real delivery by writing clean, testable, maintainable code and shipping AI services through the full software development lifecycle: build, test, deploy, monitor, and iterate.
Implement MLOps and GenAIOps practices, including CI/CD, reproducibility, environment parity, model/prompt/agent versioning, and operational readiness.
Build evaluation and observability for GenAI and agented systems, including tracing, instrumentation, regression test suites, automated scoring where appropriate, and iteration loops for prompt and policy optimization.
Design for secure enterprise deployment with access controls, auditability, handling of sensitive and PII data, and responsible AI guardrails.
Create reusable components and accelerators such as templates, evaluation harnesses, connectors, and orchestration patterns that scale across client contexts.
Thrive in a client facing consulting environment by communicating clearly with technical and non-technical stakeholders, leading working sessions, presenting recommendations, and producing concise technical documentation.
Collaborate with Bain consultants to prioritize critical technical decisions that unlock business value and support proposal shaping and scoping, including effort sizing, architecture options, risk assessment, and delivery roadmaps.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
3–5+ years of professional AI / ML engineering experience with strong backend fundamentals.
Strong Python proficiency and experience building APIs / services (REST or gRPC) and integrating with enterprise systems.
Hands-on experience delivering LLM powered applications with attention to latency, cost, reliability, and security.
Experience building advanced retrieval and search systems (hybrid retrieval, vector search, reranking) and working across multiple data stores (vector, graph, relational, document, and search platforms).
Experience implementing agentic patterns (context management, tool integration, orchestration, memory/state handling) with modern frameworks (eg, LangGraph, OpenAI Agents SDK, Pydantic AI) or custom agent loops, and sound judgment on when to apply agentic approaches.
Experience creating reusable skills, tools, and services (including MCP) for agent use, with schema validation to enforce reliable data contracts.
Strong engineering practices: testing, code review, version control, CI/CD, and performance profiling.
Experience deploying and operating services on AWS, GCP, or Azure (environment management, reliability, observability, scaling).
Experience with Docker and Kubernetes (or equivalent orchestration) and operating services in production (debugging, performance, resilience).
Proven ability to implement security, privacy, and governance requirements for AI systems (authentication/authorization, access controls, PII handling, enterprise risk controls).
Experience training, validating, and testing ML models; strong understanding of overfitting, generalization, and evaluation methodology.
Practical experience with feature engineering and data preprocessing for real world datasets.
Familiarity with a broad set of ML algorithms (classical ML and deep learning) and ability to choose methods appropriate to business and data constraints.
Familiarity with deep learning frameworks (PyTorch or TensorFlow) and ML lifecycle tooling (experiment tracking, model registry, feature store concepts).
Proven ability to operate in ambiguity and complexity, manage competing priorities, and deliver outcomes independently or with a team.
Excellent interpersonal and communication skills, with the ability to explain technical decisions, tradeoffs, and results to mixed audiences.
Strong stakeholder management skills and comfort working directly with clients.

Technologies

Python
REST, gRPC
LangGraph
OpenAI Agents SDK
Pydantic AI
PyTorch, TensorFlow
Docker, Kubernetes
AWS, GCP, Azure
MCP
Graph databases

Benefits

Bain pays 100 percent of individual employee premiums for medical, dental, and vision coverage.
Generous paid time off including parental leave, sick leave, and holidays.
Fully vested 401(k) company contribution.
Paid life and long-term disability insurance.
Annual fitness reimbursements.

What makes us a great place to work

We are consistently recognized as a leading employer in the global market, including top rankings on Glassdoor. Exceptional teams drive our strategy, and we foster an inclusive environment that welcomes diverse backgrounds, cultures, and experiences. We hire talented individuals and create conditions for professional and personal growth.

U.S. Compensation Information

In the states listed (Massachusetts, New York, District of Columbia, Georgia, Illinois, Texas, Washington, California), the good faith annualized full-time salary range for this role is $128,500 to $171,500; placement within the range varies by experience, education, and other factors.
The role includes an annual discretionary performance bonus.
4.5% 401(k) company contribution, which increases after three years of service and is 100% vested from the start date.
Some elements of discretionary compensation may apply beyond the base and bonus.
For locations outside the listed states, compensation is commensurate with competitive geographic market rates.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment.

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2d ago

GENAI / MACHINE LEARNING AI / DATA Scientist

Hudson Manpower Boston, MA 🇺🇸 Remote

Boston, MA

2d ago

Full time AI Ai Ml Amazon Bedrock

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Job Description

Hudson Manpower offers a GenAI / Machine Learning AI / Data Scientist role with 100% remote work in Boston, MA, requiring deep expertise in Python, AI/ML, DL frameworks, and cloud tools to develop prototypes, PoCs, and MVPs in GenAI.

Responsibilities

Skill sets: Ability to develop prototypes, PoCs, MVPs using one or more of the following,

Requirements

100% Remote
NO H1B Candidates REST ALL CAN APPLY
Only W2 Candidates
Experience - 10+ Years
AI/ML Knowledge: Strong foundation in AI, deep learning, and machine learning principles.
Programming Skills: Expertise in Python and tools like Hugging Face, Langchain, and OpenAI API.
Deep Learning Frameworks: Experience with TensorFlow, Keras, and PyTorch.
Cloud Platforms: Familiar with Google Model Garden, Amazon Bedrock, and Nvidia Nim.
Multi-Modal Data and AI Tools: Experience with multi-modal data and intelligent agent-based tools.
Mindset: Self-motivated individual with a passion for solving hard problems using AI/GenAI. Must have collaborative and an innovative mindset.

Technologies

Python
Hugging Face
Langchain
OpenAI API
TensorFlow
Keras
PyTorch
Google Model Garden
Amazon Bedrock
Nvidia Nim

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3d ago

Lead Data Engineer

Daley and Associates Boston, MA

Boston, MA

3d ago

Full time Cloud Cloud Platform Data

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Job Description

Daley and Associates is seeking a Lead Data Engineer to own the development of data integration, dbt-driven data modeling in Snowflake, and the construction of end-to-end data pipelines that empower investment data analytics. This onsite role in Boston, MA requires a collaborative leader who can support the Investment Data Management Office three days per week while driving scalable solutions that align with architectural standards.

Responsibilities

Develop and maintain dbt models inside Snowflake, embedding business logic and ensuring alignment with the existing architecture and data standards.
Oversee and contribute to dbt projects, maintaining code quality, documentation, and modular, scalable design patterns.
Design, build, and administer scalable data pipelines and a robust data warehouse to support reporting, analytics, and operational use cases.
Lead development efforts and implement solutions that meet business requirements and support program objectives.
Drive continuous improvement of data quality, resiliency, control, efficiency, and monitoring capabilities.
Troubleshoot complex system interactions to identify root causes of issues.
Collaborate with the platform lead to design, develop, implement, and deploy new software components on the investment data platform.
Partner with the data architect to evaluate and finalize a unified data model.
Work with the integration architect to upgrade and integrate data ingestion and delivery tools within the unified platform.
Upgrade and integrate transformation, data validation, and orchestration tools to enable data engineering, analytics, and maintenance tasks.
Provide on-call support during unexpected outages.

Requirements

Bachelor’s degree in Computer Science or related disciplines.
5-6+ years designing, developing, and delivering data-centric, complex applications.
2-4+ years of hands-on work from SQL to Advanced SQL.
Experience developing and maintaining data models using dbt (Data Build Tool).
Background in data integration (ETL/ELT), data warehousing, analytics architecture, with familiarity in Snowflake and other cloud-native databases.
Development experience on cloud PAAS platforms such as Microsoft Azure, Google Cloud Platform, or Amazon Web Services.
Strong understanding of Agile SDLC, DevOps, and cloud technologies, with exposure to multiple technologies and environments.
Knowledge of architectures and patterns such as unified data management, data mesh, event-driven architectures, real-time data flows, non-relational repositories, and data virtualization.
Experience building solutions in the financial services domain with an understanding of financial instruments, transactions, and positions is desirable.
Solid interpersonal and communication skills with the ability to lead cross-team collaborations.

Technologies

dbt (Data Build Tool)
Snowflake
Microsoft Azure
Google Cloud Platform
Amazon Web Services

What we are looking for

Bachelor’s degree in Computer Science or related disciplines.
5-6+ years designing, developing, and delivering data-oriented, complex applications.
2-4+ years of progressive SQL experience, including advanced SQL.
Proven experience developing and maintaining data models with dbt.
Background in data integration (ETL/ELT), data warehousing, and analytics architecture; familiarity with Snowflake and other cloud-native databases.
Experience developing on cloud PAAS platforms such as Azure, GCP, or AWS.
Deep grasp of Agile SDLC, DevOps, and cloud technologies, with exposure to diverse technologies and environments.
Knowledge of unified data management, data mesh, event-driven, real-time data flows, and related architectures.
Experience in financial services data solutions, including instruments, transactions, and positions, is desirable.
Strong collaboration and communication skills to work across internal and external teams.

Preferred Qualifications

Experience in the asset management and investment data domain, including multi-asset platforms and related data ecosystems.
Understanding of asset management concepts and familiarity with various financial instruments and products.
Industry certifications in Snowflake, dbt, cloud data engineering, data warehousing, or financial markets are highly valued.
Interest in emerging AI technologies and how AI-driven tools can enhance engineering workflows, data quality, and analytics.
Familiarity with AI-assisted development, automation, or data engineering best practices to boost productivity.

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5d ago

Databricks Data Engineer II

Deloitte Boston, MA

Boston, MA

5d ago

$87k - $171k/yr Full time Big Data Cloud Platform Data Analytics

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Job Description

The Databricks Data Engineer II role at Deloitte focuses on designing and optimizing cloud-based data pipelines and platforms to support analytics and AI initiatives. You will collaborate with business and technology teams to modernize data environments and enable data-driven decision making.

Job Details

Location: Boston, MA (onsite)
Salary: USD 86,700 - 170,900 per year
Minimum experience: 3 years
Education: Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or Statistics

Role Overview

The role centers on designing, building, and refining Databricks based data pipelines and engineering solutions to support analytics and artificial intelligence initiatives. It emphasizes cloud-native data ingestion, transformation, and storage patterns to modernize enterprise data platforms.

Responsibilities

Architect and implement data pipelines and engineering solutions using Databricks, Apache Spark, Python, and SQL
Assist in modernizing enterprise data platforms by applying cloud-based ingestion, transformation, and storage patterns
Create and maintain batch and streaming workflows that support reporting, analytics, and AI use cases
Apply data architecture, integration, and modeling practices to improve data quality, scalability, and performance
Collaborate with client and Deloitte teams to troubleshoot issues, implement enhancements, and support large-scale data transformation programs

Requirements

Ability to work independently and as part of a team
Strong written and verbal communication skills
Attention to detail and a commitment to quality
Demonstrated ability to build and maintain professional relationships
Capability to lead projects or workstreams
Skill in managing multiple tasks in a fast-paced environment
Professional demeanor and strong interpersonal skills
Ability to meet deadlines and deliver results
Ability to provide clear guidance to others
Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or Statistics
3+ years of experience in data engineering, ETL development, or data platform engineering
2+ years of experience building data pipelines in Databricks using Spark, Python, and SQL
Experience implementing data models, data integration patterns, and cloud-based data processing workflows
Experience with at least one cloud platform: AWS, Azure, or Google Cloud Platform (GCP)
Ability to travel approximately 50% depending on assignments
Limited immigration sponsorship may be available

Technologies

Databricks
Apache Spark
Python
SQL
Delta Lake
Databricks Workflows
Unity Catalog
Git
CI/CD pipelines
AWS
Azure
Google Cloud Platform (GCP)

The Team

Deloitte's Core AI and Data practice helps organizations modernize data platforms, reinforce enterprise data foundations, and scale analytics and AI capabilities across the business. The team architects, engineers, and deploys cloud-based data solutions to improve decision-making, foster innovation, and support large-scale transformations. Practitioners collaborate across business and technology functions to address complex data modernization challenges.

Information for Applicants with a Need for Accommodation

For applicants requiring accommodations, Deloitte provides assistance. See the following page for details: Join Deloitte: Assistance for Disabled Applicants.

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6d ago

AI Data Scientist Senior Associate

PRICE WATERHOUSE COOPERS Boston, MA

Boston, MA

6d ago

$72k - $212k/yr Full time Senior Analytics Artificial Intelligence

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Job Description

Senior AI Data Scientist Associate at PwC in Boston, MA (onsite) leverages advanced analytics, statistical modeling, and machine learning to turn raw data into actionable insights for decision-making and business growth, with a salary range of USD 72,000 - 212,000 per year.

Responsibilities

Apply advanced analytics and statistical methods to extract insights from large datasets.
Design and deploy robust data solutions to convert raw data into actionable insights.
Perform exploratory and descriptive analyses to inform strategic decisions.
Utilize machine learning algorithms and predictive modeling to address complex business challenges.
Create data visualizations that clearly communicate insights and support data‑driven decisions.
Collaborate with clients to understand data needs and deliver tailored solutions.
Manage data pipelines and ensure data quality and integrity throughout the analysis process.
Implement data science workflows and troubleshooting techniques to optimize performance.
Commit to continuous learning to deepen technical skills and adapt to emerging technologies.
Mentor junior team members and foster a collaborative team environment.
Apply statistical analysis, machine learning, data preparation, experimentation, and model evaluation to develop and validate AI/ML solutions.
Use Python, data science libraries, model validation methods, and modern AI/ML approaches (including generative AI where relevant) to communicate actionable insights to business and technical stakeholders.
Demonstrate proficiency in data science algorithms and workflows.
Leverage machine learning and deep learning techniques effectively.
Excel in complex data analysis and predictive modeling.
Leverage experience with data engineering and data pipelines.
Apply knowledge of natural language processing and neural networks.
Navigate ambiguity while building meaningful client relationships.

Requirements

Bachelor’s degree required.
Minimum of 2 years of professional experience.

Technologies

Python
Generative AI
Neural networks
Natural language processing
Deep learning

Benefits

Annual discretionary bonus
Medical insurance
Dental insurance
Vision insurance
401k
Holiday pay
Vacation
Personal and family sick leave

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11d ago

Lead Research Data Scientist

Publicis Groupe Holdings B.V Boston, MA

Boston, MA

11d ago

Full time Analytics Artificial Intelligence Big Data

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Job Description

The Lead Research Data Scientist position is based onsite in Boston, MA, and sits within Epsilon's Decision Sciences IQ team. The role focuses on building automated segmentation, predictive modeling, and GenAI solutions for the PeopleCloud marketing SaaS, with responsibility for productionizing ML solutions and collaborating with engineering to embed them into the platform.

Responsibilities

Lead projects from initial research through development in collaboration with stakeholders
Develop familiarity with DSIQ's modeling platform and Epsilon's proprietary datasets
Apply data science and machine learning expertise to investigate and propose optimal approaches for technology and business challenges
Design, implement, and validate scalable analytic pipelines using tools such as Databricks, Spark, Python, MLlib, Keras, TensorFlow, Git, Jira, and Confluence
Collaborate with Engineering teams to integrate solutions into Epsilon's PeopleCloud SaaS offerings
Engage in the team's collaborative culture by sharing knowledge, debating techniques, and pursuing research to advance collective capabilities

Requirements

Ph.D. in Computer Science, Statistics, Linguistics, Electrical Engineering, Mathematics, Economics, Physics, Operations Research, or a related scientific field
Demonstrated research experience and coursework in Machine Learning
At least 1 year of experience managing research and development projects
At least 2 years of relevant programming experience gained through academic research, internships, or industry work
Strong Python programming skills with experience in research or production code
Experience working with large datasets
Solid understanding of modeling and statistical techniques
Desire to contribute in a highly collaborative environment
Excellent communication and interpersonal abilities for conveying ideas and complex solutions

Technologies

Databricks
Spark
Python
MLlib
Keras
TensorFlow
Git
Jira
Confluence
Hadoop
AWS
LLMs
Agentic frameworks

Additional Skills

Experience with distributed and cloud computing platforms such as Hadoop, Spark, AWS, Databricks, or related technologies
Experience with SQL and Python
Familiarity with using LLMs and agentic frameworks
Experience in Natural Language Processing, Information Retrieval, Mathematical Optimization, Control Theory, Time-Series Analysis, or Causal Inference

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12d ago

Robotics Automation Data Scientist

Home Depot / THD Boston, MA

Boston, MA

12d ago

$125k - $175k/yr Full time Analytics Automation Business Intelligence

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Job Description

As a Robotics Automation Data Scientist, you will join Home Depot's THD robotics organization in Boston to translate on the ground data from automated warehouse systems into actionable insights. The role centers on applying business intelligence, advanced analytics, and optimization to improve throughput, robot utilization, inventory flow, and order fulfillment across deployments. This onsite position offers a compensation range of USD 125,000 - 175,000 per year.

Responsibilities

Create and sustain operational dashboards and reporting systems.
Define and track KPIs across customer deployments.
Produce executive, operational, and customer-facing performance reports.
Analyze trends, anomalies, and performance dips in warehouse operations.
Translate complex operational data into clear business recommendations.
Examine warehouse workflows to pinpoint bottlenecks and inefficiencies.
Monitor warehouse throughput
Monitor robot utilization
Monitor inventory flow
Monitor pick productivity
Monitor station efficiency
Monitor order cycle time
Monitor resource allocation
Monitor labor productivity
Evaluate the impact of software releases and operational changes on customer performance.
Measure system-wide performance and identify optimization opportunities.
Analyze robotic fleet performance and utilization patterns.
Identify congestion points and traffic inefficiencies.
Evaluate task assignment effectiveness.
Measure robot travel efficiency and idle time.
Develop recommendations to improve fleet coordination and throughput.
Build predictive and diagnostic analytical models.
Develop forecasting models for order volume.
Develop forecasting models for inventory demand.
Develop forecasting models for capacity planning.
Develop forecasting models for resource utilization.
Support operational planning through scenario analysis.
Create models that enable proactive issue identification.
Design and analyze A/B tests and operational experiments.
Measure effectiveness of software enhancements and workflow changes.
Partner with Product and Engineering teams to validate hypotheses using data.
Quantify ROI for optimization initiatives.
Collaborate with engineering teams to improve data collection and instrumentation.
Define operational metrics and data standards.
Ensure data quality, consistency, and reliability.
Support development of data pipelines and analytics infrastructure.
Analyze customer deployment performance.
Produce operational health assessments.
Identify opportunities for customers to improve utilization of automation systems.
Support customer success and deployment teams with performance analysis.
Orders processed per hour
Inventory movement efficiency
Pick rates
Put rates
Cycle count accuracy
Order completion times
Travel efficiency
Congestion reduction
Queue management
Task completion rates
Fleet balancing
Workflow latency
Service response times
Throughput capacity
Resource consumption
Exception rates
Operational uptime

Requirements

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Industrial Engineering, Operations Research, or a related field.
3+ years of experience in data analytics, business intelligence, data science, or operational optimization.
Strong SQL skills with experience handling large datasets.
Proficiency in Java or Kotlin.
Experience working with streaming data sources such as Kafka or MQTT.
Experience developing dashboards and performance reports.
Strong statistical analysis and problem-solving abilities.
Ability to communicate technical findings to business and operational stakeholders.