data science engineer

Fidelity Investments

<div><h3 class="jobSectionHeader"><b>Job Description:</b></h3><p><b>
Principal Data Science Engineer - Financial Crimes</b></p><p><b>
The Role</b>
</p><p><b>Financial Crimes Models &amp; Analytics </b>is seeking a <b>Principal Data Science Engineer </b>to lead the design, development, and optimization of our transaction monitoring surveillance models.
</p><p>You will partner with our Data Scientists, Business Intelligence analysts, Investigators, and Compliance professionals to translate regulatory requirements into scalable, rules based &amp; machine learning detection models. <b>This role requires a unique blend of banking, brokerage, anti-money laundering (AML) &amp; fraud knowledge, as well as data analysis, data engineering, and AI/ML expertise.
</b></p><p>If you&rsquo;re passionate about feature engineering, analytics, and machine learning to help fight financial crime, this is an excellent opportunity for you!
</p><p><b>The responsibilities of this role:</b></p><ul><li>
Collaborate with team members and compliance partners to understand<b> AML typologies</b> and <b>red flags</b> we must detect
</li><li>Assist in building detection models and features using <b>SQL, Python, DBT</b> (Data Build Tool), and <b>Snowflake</b>
</li><li>Develop detection models using both rules-based and machine learning algorithms on customer, account, and transaction data
</li><li>Apply machine learning and AI techniques to enhance suspicious activity detection by analyzing and identifying appropriate target data.
</li><li>Monitor and optimize model performance using proper ML Operations tools
</li><li>Help drive AI use cases for investigative workflows including integration in alert management systems, narrative generation, and straight through SAR filing
</li><li>Champion best practices for CI/CD, robust automated testing, model performance, and production monitoring
</li><li>Provide technical leadership, mentoring and training to other team members through code reviews, collaboration, and educational presentations
</li><li>Explore new technologies (e.g., anomaly detection, graph analytics, predictive modeling) and determine their applicability to the team&rsquo;s use cases; orchestrate the adoption of such technologies and trends where appropriate
</li></ul><p><b>The Expertise and Skills You Bring</b></p><p><b>
Required Qualifications</b>
</p><ul><li><b>Bachelor&rsquo;s degree in Computer Science </b>or equivalent technical discipline.
</li><li><b>6+ years</b> of experience in software or data engineering, including leading and delivering complex projects.
</li><li><b>Strong proficiency in Python </b>or at least one object-oriented programming language (e.g., Java) with a focus on writing clean, modular, and testable code.
</li><li>Strong experience querying <b>relational databases</b> (e.g., Oracle, Snowflake) and working with non-relational databases (e.g., MongoDB).
</li><li>Hands-on experience with <b>machine learning algorithms</b>, including decision trees, neural networks, regression models, clustering, and anomaly detection.
</li></ul><p><b>Preferred Skills</b>
</p><ul><li><b>Domain expertise</b>: Prior experience working with customer and transactional data in the fraud or AML space.
</li><li><b>Digital assets knowledge</b>: Understanding blockchain technologies; prior experience in cryptocurrency monitoring is a plus.
</li><li>Experience with <b>dbt (data build tool)</b> for data transformation and pipeline development.
</li><li>Prior experience developing solutions using <b>large language models (LLMs)</b>, including <b>Retrieval-Augmented Generation (RAG)</b> for information retrieval and workflow automation.
</li><li>Certifications such as CAMS (Certified Anti-money Laundering Specialist) or CFE (Certified Fraud Examiner) are desirable
</li></ul><p><b>The Team</b>
</p><p>Financial Crimes Models &amp; Analytics is made up of Data Scientists, Data Engineers, Business Intelligence, and Data Visualization analysts. Our team has broad responsibility for Fidelity Investments transaction monitoring across multiple business units, including Brokerage and Digital Assets. We leverage data to detect potential suspicious activity, customer behavior changes, and more.
</p><p>Coverage areas include insider trading, high risk money movement, customer behavior &amp; potentially suspicious transactional patterns, elder financial exploitation, low-priced securities, emerging risks, cryptocurrency transactions and many more.
</p>The base salary range for this position is $107,000-216,000 USD per year.
<p>Placement in the range will vary based on job responsibilities and scope, geographic location, candidate&rsquo;s relevant experience, and other factors.</p><p>
Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.
</p><p>We offer a wide range of benefits to meet your evolving needs and help you live your best life at work and at home. These benefits include comprehensive health care coverage and emotional well-being support, market-leading retirement, generous paid time off and parental leave, charitable giving employee match program, and educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career. Note, the application window closes when the position is filled or unposted.</p><p>
Please be advised that Fidelity&rsquo;s business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.</p><p>
Most roles at Fidelity are Hybrid, requiring associates to work onsite every other week (all business days, M-F) in a Fidelity office. This does not apply to Remote or fully Onsite roles. Please consult with your recruiter for the specific expectations for this position.</p><h3 class="jobSectionHeader"><b>
Certifications:</b></h3><h3 class="jobSectionHeader"><b>
Category:</b></h3>
Data Analytics and Insights</div>

Principal Data Science Engineer - Financial Crimes

Siemens Energy

<div><div><b>A Snapshot of Your Day</b></div><div></div><div><br>
Imagine starting your day by diving into the core of next‑generation gas turbine innovation. You collaborate closely with colleagues to design and refine damage‑tolerant methodologies that ensure the reliability of massive turbine systems. Your work moves fluidly between developing mechanical integrity software, automating engineering workflows, and evaluating real component behavior under demanding conditions like fatigue, fracture, and creep. In between analytical deep dives, you prepare clear technical documents and presentations that help guide design decisions and keep projects on track in terms of time, cost, and quality. Every day, you contribute to making complex turbine components safer, more efficient, and more resilient.</div><div></div><div><b><br>
How You&rsquo;ll Make an Impact</b></div><div><ul><li>
Develop design methods and software supporting damage‑tolerant design for large gas turbine systems</li><li>
Apply mechanical integrity concepts&mdash;including fatigue, fracture mechanics, creep, and uncertainty analysis&mdash;to evaluate turbine components</li><li>
Plan, program, and automate engineering workflows related to mechanical integrity methods and technologies</li><li>
Assess component behavior across different failure mechanisms, such as LCF/TMF, HCF, fracture, and creep</li><li>
Support design projects by preparing engineering documents and presentations that communicate technical results</li><li>
Collaborate with teams and interface with manufacturing‑related processes, leveraging familiarity with manufacturing and quality assurance where applicable</li></ul></div><div><b>
What You Bring</b></div><div><ul><li>
Master's degree in mechanical engineering, aeronautical engineering, aerospace engineering or related field</li><li>
Advance knowledge and strong background in mechanical integrity, including fatigue and fracture mechanics</li><li>
3+ years of experience in gas turbine industry or turbomachinery applications</li><li>
Long-standing, in-depth knowledge of finite element analysis (FEA) (Ansys, Abaqus, or similar software)</li><li>
Technical tool proficiency, including CAD systems (e.g., NX), programming (Python, C++, Linux), and exposure to HPC/cloud simulation environments (Azure, AWS)</li><li>
Excellent analytical, interpersonal, and communication skills, with familiarity in manufacturing support and supplier data exchange</li><li>
Applicants must be legally authorized for employment in the United States without need for current or future employer-sponsored work authorization. Siemens Energy employees with current visa sponsorship may be eligible for internal transfers.</li></ul></div><div><b>
About the Team</b></div><div></div><div><br>
Our Gas Services division offers Low-emission power generation through service and decarbonization. Zero or low emission power generation and all gas turbines under one roof, steam turbines and generators. Decarbonization opportunities through service offerings, modernization, and digitalization of the fleet.</div><div></div><div><b><br>
Who is Siemens Energy?</b></div><div></div><p><br>
At Siemens Energy, we are more than just an energy technology company. With ~100,000 dedicated employees in more than 90 countries, we develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in our research departments and factories drive the energy transition and provide the base for one sixth of the world's electricity generation.</p><p><br>
Our global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation.<br>
</p><div></div><br>
<div>Find out how you can make a difference at Siemens Energy: https://www.siemens-energy.com/employeevideo</div><div></div><div><b><br>
Rewards/Benefits</b></div><div><ul><li>
Career growth and development opportunities; supportive work culture</li><li>
Company paid Health and wellness benefits</li><li>
Paid Time Off and paid holidays</li><li>
401K savings plan with company match</li><li>
Family building benefits</li><li>
Parental leave</li></ul></div><div></div><div><br>
https://jobs.siemens-energy.com/jobs</div><div></div><div><br>
#RPO #LGTEN #ELECTRON</div></div>

Mechanical Integrity and Data Science Engineer (Gas Turbines)

Coherent Corp.

<p></p><div><p><b>Primary Duties &amp; Responsibilities
</b></p><ul><li>Work closely with domain experts to support assigned analytics and data science projects.
</li><li>Collect, clean, preprocess, and validate structured and unstructured datasets from multiple sources such as log parsing, text file parsing, instrument data streams and existing databases, etc.
</li><li>Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
</li><li>Create technical documentation, reports, and presentations summarizing findings, insights, and recommendations.
</li><li>Assist with selection, evaluation, and setup of data science tools, libraries, and computing resources.
</li><li>Follow best practices for data governance, version control, and reproducible research.
</li><li>Collaborate within a cross-functional team environment and contribute to continuous improvement initiatives.
</li></ul><p><b>Education &amp; Experience
</b></p><ul><li>B.S. preferred, working towards a graduate degree in Optical Engineering, Laser Physics, Mechatronics, Mechanical Engineering, Computer Science, Data Science, Electrical Engineering, or related fields. Excellent final year BS students will be considered.
</li><li>Relevant coursework or extracurricular experience in Data science is a plus.
</li>Open to currently enrolled students or those who have graduated within one year of the internship start date.<br>
<li>
</li></ul><p></p><p><b>Skills &amp; Other Requirements
</b></p><ul><li>Programming experience in C#, Python, R, or similar languages.
</li><li>Familiarity with data analysis libraries such as pandas, NumPy, SciPy, scikit-learn, or equivalent.
</li><li>Expert knowledge of SQL DB and relational databases.
</li><li>Understanding basic statistical concepts and machine learning techniques.
</li><li>Experience with Jupyter notebooks, Git/version control.
</li><li>Familiarity with Microsoft Azure cloud infrastructure is a plus.
</li><li>Familiarity with diagnostic and signal acquisition tools such as oscilloscopes, signal generators, ADC and data acquisition systems.
</li><li>The ideal candidate will be an enthusiastic self-starter who takes ownership of commitments and enjoys working in a dynamic collaborative team environment.
</li><li>Excellent written and verbal communication.
</li><li>Team-oriented but able to work independently when needed.
</li><li>Adaptable and eager to learn in a fast-paced environment.
</li>Attention to detail and time management.<br>
<li>
</li></ul><p></p><div><div><div><div><b>Additional Information
</b></div></div><br>
</div></div><ul><li>Internship Duration: 10 &ndash; 14 weeks.
</li><li>At Coherent, interns are valued members of our team and have the opportunity to make meaningful contributions from day one. In addition to hands-on project experience, our internship program includes opportunities to connect with fellow interns and colleagues across the organization through virtual and in-person networking events, team-building activities and more. Interns are expected to actively participate in these events as part of their professional development and to fully immerse themselves in our collaborative and innovative culture.
</li></ul><p><b>Working Conditions
</b></p><ul><li>This role will be based on site in Bloomfield, CT
</li><li>Regular use of a computer and other office equipment is necessary.
</li><li>On site in engineering/optics laboratory
</li></ul><p><b>Physical Requirements
</b></p><ul><li>Sitting for extended periods while working on a computer or in meetings.
</li><li>Use of hands and fingers for typing, writing, and handling documents.
</li><li>Occasional lifting of objects or materials up to 20 pounds for administrative tasks.
</li><li>Ability to communicate verbally and in writing.
</li></ul><p><b>Safety Requirements
</b></p><p>All employees are required to follow the site EHS procedures and Coherent Corp. EHS standards.
</p><p><b>Quality &amp; Environmental Responsibilities
</b></p><p>Depending on location, this position may be responsible for the execution and maintenance of the ISO 9000, 9001, 14001 and/or other applicable standards that may apply to the relevant roles and responsibilities within the Quality Management System and Environmental Management System.
</p><p><b>Culture Commitment
</b></p><p>Ensure adherence to company&rsquo;s values (ICARE) in all aspects of your position at Coherent Corp.:
</p><p>Integrity &ndash; Create an Environment of Trust
</p><p>Collaboration &ndash; Innovate Through the Sharing of Ideas
</p><p>Accountability &ndash; Own the Process and the Outcome
</p><p>Respect &ndash; Recognize the Value in Everyone
</p><p>Enthusiasm &ndash; Find a Sense of Purpose in Work
</p><p>Coherent Corp. is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.
</p><p>If you need assistance or an accommodation due to a disability, you may contact us at talentacquisition@coherent.com.
</p><p><b>ABOUT US
</b></p><p>Coherent is a global leader in lasers, engineered materials and networking components. We are a vertically integrated manufacturing company that develops innovative products for diversified applications in the industrial, optical communications, military, life sciences, semiconductor equipment, and consumer markets. Coherent provides a comprehensive career development platform within an environment that challenges employees to perform at their best, while rewarding excellence and hard-work through a competitive compensation program. It's an exciting opportunity to work for a company that offers stability, longevity and growth. Come Join Us!
</p><p>Note to recruiters and employment agencies: We will not pay for unsolicited resumes from recruiters and employment agencies unless we have a signed agreement and have required assistance, in writing, for a specific opening.</p></div><p></p>
<br>ABOUT US
<br><div>Coherent is a global leader in lasers, engineered materials and networking components. We are a vertically integrated manufacturing company that develops innovative products for diversified applications in the industrial, optical communications, military, life sciences, semiconductor equipment, and consumer markets. Coherent provides a comprehensive career development platform within an environment that challenges employees to perform at their best, while rewarding excellence and hard-work through a competitive compensation program. It's an exciting opportunity to work for a company that offers stability, longevity and growth. Come Join Us!
<br>
<br>
<b>Note to recruiters and employment agencies: </b>We will not pay for unsolicited resumes from recruiters and employment agencies unless we have a signed agreement and have required assistance, in writing, for a specific opening.</div>

INTERN: Data Science Software Engineer

Tata Consultancy Services (TCS)

<div></div><div><div><div><div><div>Must Have Technical/Functional Skills</div><br>
<div>
</div><div></div><ul><li> Data Engineers &amp; Data Scientists
</li></ul><ul><li> Exceptional Python and Spark SQL knowledge
</li></ul><ul><li> Strong knowledge of Databricks and cloud architecture
</li></ul><ul><li> Ability to influence technical and non-technical individuals including UDAP admins
</li></ul><ul><li> Knowledge of workflows, compute, key vaults, catalogs, objects, etc.
</li></ul><ul><li> Strong knowledge of ServiceNow data and how it ties together
</li></ul><ul><li> Knowledge of data science best practices including when to use which model
</li></ul><ul><li> Reporting and Analytics Professionals:
</li></ul><ul><li> Strong Spark SQL knowledge
</li></ul><ul><li> Strong Power BI knowledge
</li></ul><ul><li> Strong visualization skills and communication skills
</li></ul><ul><li> Ability to interpret ambiguous requirements from non-technical requestors
</li></ul><ul><li> Power Apps knowledge
</li></ul><div>Roles &amp; Responsibilities
</div><ul><li> Design, build, and deliver data science solutions to the IT organization based on the Next Gen ServiceNow Data Store
</li></ul><ul><li> Continued iteration and support for existing data science solutions (CQR, ATX Incidents, Onboarding Incidents, etc.)
</li></ul><ul><li> Design, build, implement chat bot across Next Gen ServiceNow Data Store
</li></ul><ul><li> Identify high value data science projects (knowledge, incident, etc.) and deliver on those
</li></ul><ul><li> Monitoring accuracy and precision of data science solutions
</li></ul><ul><li> Enable users, both technical and non-technical, to use a chatbot to gather insights on the data store</li></ul><div><br>
</div>
<div></div><br>
<div>Salary Range $120,000-$140,000 years
</div>
<div></div><div>TCS Employee Benefits Summary:
</div><div>Discretionary Annual Incentive.
</div><div>Comprehensive Medical Coverage: Medical &amp; Health, Dental &amp; Vision, Disability Planning &amp; Insurance, Pet Insurance Plans.
</div><div>Family Support: Maternal &amp; Parental Leaves.
</div><div>Insurance Options: Auto &amp; Home Insurance, Identity Theft Protection.
</div><div>Convenience &amp; Professional Growth: Commuter Benefits &amp; Certification &amp; amp; Training Reimbursement.
</div><div>Time Off: Vacation, Time Off, Sick Leave &amp; Holidays.
</div><div>Legal &amp; Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
</div>
<div></div><div>#LI-SP1
</div></div></div></div><div><div><div><b>Location</b></div>
<div>Louisville, KY</div>
</div><div><div><b>Job Function</b></div>
<div>TECHNOLOGY</div>
</div><div><div><b>Role</b></div>
<div>Engineer</div>
</div><div><div><b>Job Id</b></div>
<div>401874</div>
</div><div><div><b>Desired Skills</b></div>
<div>Data Science</div>
</div><div><div><b>Salary Range</b></div>
<div>$120,000-$140,000 a year</div>
</div></div><p>Desired Candidate Profile
</p><div><div><b>Qualifications</b> : BACHELOR OF COMPUTER SCIENCE</div></div></div><div></div>

IT Service Management Data Engineer

Cambium Biomaterials

<div><p>AI Data Platform / Pipeline Engineer</p><p>
(Full-time, onsite in El Segundo, CA &mdash; U.S. citizenship required due to the nature of our work)</p><p>
About Cambium</p><p>
Cambium is an advanced materials startup building next generation polymer and composite systems for aerospace, defense, and critical industries. We combine physics-based modeling, experimentation, and cutting-edge AI&mdash;including multimodal foundation models&mdash;to accelerate materials discovery and deployment.</p><p>
Role Summary</p><p>
We are seeking an AI Data Platform + MLOps engineer to build the pipelines, infrastructure, and automation that powers our AI foundation models, computational chemistry, and operational tools. You will build the data backbone that accelerates foundation model development and drives AI deployment into real manufacturing and operational workflows&mdash;with a mandate to reduce friction, eliminate manual pipelines, and enable rapid iteration.</p><p>
Key Responsibilities</p><ul><li>Build robust pipelines for chemistry, materials, and manufacturing data ingestion and transformation.</li><li>Define data contracts, dataset versioning, and labeling/standardization workflows.</li><li>Operate ETL/training orchestration, experiment tracking, model registry, and deployment automation.</li><li>Manage cloud workflows (Azure + GCP), reproducible environments, monitoring, and cost/performance tuning.</li><li>Connect R&amp;D and Ops systems (ELN/LIMS/ERP/MES) into unified data flows.</li></ul><p>
Qualifications</p><ul><li>10+ years in data science, Dev/Ops, MLOps, or data engineering in an operational setting</li><li>Expert data pipelines, data tech stacks, orchestration, and MLOps/DevOps tooling.</li><li>Ability to design resilient, scalable pipelines in ambiguous, fast-moving environments.</li><li>Strong systems thinking, requirements gathering, and cross functional collaboration skills.</li><li>Familiarity with scientific or manufacturing data is a plus.</li></ul><p></p><p><br>
BENEFITS</p><p>
Cambium offers a highly competitive compensation and benefits plan. This includes excellent medical/dental/vision benefits, and a matching 401(k) plan, professional development reimbursement, and an opportunity for equity for most full time positions.</p><p>
As a condition of employment, the candidate may need to successfully complete a medical evaluation and obtain clearance to wear respiratory personal protective equipment (PPE) as required by OSHA 29 CFR 1910.134</p></div>

AI Data Platform/Pipeline Engineer

Apple

<div>Do you love the challenge of solving complex problems that can have a direct and meaningful impact on the company? Do you want to be part of a supportive team that&rsquo;s constantly learning and having fun while solving tough business problems? We&rsquo;d love to talk to you if you do!<br>
<br>
At Apple, new ideas have a way of quickly becoming outstanding products, services, and customer experiences. Bring passion and dedication to your career, and there's no telling what you could accomplish! Strategic Data Solutions empowers internal partners and optimizes the customer experience by delivering data-driven solutions that mitigate fraud, improve security, and optimize efficiency. Our work touches all parts of Apple, from manufacturing to fulfillment to apps and services. The enormous scale and complexity of the problems and our data present exciting opportunities for pushing the limits of existing data science methods.<br>
<br>
As a SDS Machine Learning Engineer, you will work with teams across Apple, using data analysis and predictive modeling techniques to define, build, deploy, and maintain end-to-end operational solutions that have a direct and measurable impact to the company and our customers.<br>
<br>
Our commitment to you: We will provide challenging problems that will engage your curiosity. We will provide an organizational culture that values collaboration, problem-solving, and work-life balance. We will provide mentorship to further develop your technical and leadership skills.<br>
<br>
<b>Description</b><br>
<br>
<ul><li>Engage with stakeholders to translate ambiguous business problems into technical solutions, including finding opportunities, breaking them into solvable segments, defining requirements, assessing level of effort, etc</li></ul><br>
<ul><li>Work cooperatively to design data science-driven solutions, balancing the utility of tried-and-true techniques and the benefits of custom solutions</li></ul><br>
<ul><li>Collaborate with technical partners to implement robust real-time and batch decisioning in production</li></ul><br>
<ul><li>Create reporting and monitor decisioning quality to maintain operational and business metric health</li></ul><br>
<ul><li>Investigate trends, assess threat impact, and respond with agile logic changes</li></ul><br>
<ul><li>Communicate with stakeholders with varying technical backgrounds and business priorities about your work</li></ul><br>
<ul><li>Share what you're learning about novel technologies and methods (in data science, machine learning, data engineering, and software engineering, etc) to improve your team's overall technical capabilities</li></ul><br>
<b>
Preferred Qualifications</b><br>
<br>
Theoretical understanding of machine learning algorithms and their relative strengths and weaknesses<br>
<br>
Ability to use a querying language such as SQL to extract insights from data<br>
<br>
Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact<br>
<br>
Effective communication skills to translate complex concepts and analysis into concise, business-focused solutions<br>
<br>
Team-oriented skills and values to facilitate effective collaboration with business and technical partners<br>
<br>
<b>Minimum Qualifications</b><br>
<br>
Graduate degree with research/work experience utilizing data science techniques (including but not limited to Computer Science, Statistics, Political Science, Biology, etc) or Bachelor&rsquo;s degree with equivalent experience<br>
<br>
At least 3 years of practical experience (acquired through work, independent projects, or academic research) in deploying machine learning solutions to answer real-world questions<br>
<br>
Practical experience with implementing data science-related applications in a programming language such as Python, Scala, or Java<br>
<br>
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .</div>

Machine Learning Engineer - Strategic Data Solutions

Fusemachines

<div>
 <strong>
  About Fusemachines
  <br/>
  <br/>
 </strong>
 Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients&rsquo; AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government.
 <br/>
 <br/>
 Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.
 <br/>
 <br/>
 <strong>
  Salary Range:
 </strong>
 US$ 140,000-190,000/year
 <br/>
 <br/>
 <strong>
  Role Overview
  <br/>
  <br/>
 </strong>
 We&rsquo;re hiring a mid-to-senior Machine Learning Engineer / Data Scientist to build and deploy machine learning solutions that drive measurable business impact. You&rsquo;ll work across the ML lifecycle&mdash;from problem framing and data exploration to model development, evaluation, deployment, and monitoring&mdash;often in partnership with client stakeholders and internal delivery teams.
 <br/>
 <br/>
 You should be strong in core data science and applied machine learning, comfortable working with real-world data, and capable of turning modeling work into production-ready systems.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Problem Framing &amp; Stakeholder Partnership
  </li>
  <ul>
   <li>
    Translate business questions into ML problem statements (classification, regression, time series forecasting, clustering, anomaly detection, recommendation, etc.)
   </li>
   <li>
    Collaborate with stakeholders to define success metrics, evaluation plans, and practical constraints (latency, interpretability, cost, data availability)
   </li>
  </ul>
  <li>
   Data Analysis &amp; Feature Engineering
  </li>
  <ul>
   <li>
    Use SQL and Python to extract, join, and analyze data from relational databases and data warehouses
   </li>
   <li>
    Perform data profiling, missingness analysis, leakage checks, and exploratory analysis to guide modeling choices
   </li>
   <li>
    Build robust feature pipelines (aggregation, encoding, scaling, embeddings where appropriate) and document assumptions
   </li>
  </ul>
  <li>
   Model Development (Core ML)
  </li>
  <ul>
   <li>
    Train and tune supervised learning models for tabular data (e.g., logistic/linear models, tree-based methods, gradient boosting such as XGBoost/LightGBM/CatBoost, and neural nets for structured data)
   </li>
   <li>
    Apply strong tabular modeling practices: handling missing data, categorical encoding, leakage prevention, class imbalance strategies, calibration, and robust cross-validation
   </li>
   <li>
    Build time series models (statistical and ML/DL approaches) and validate with proper backtesting
   </li>
   <li>
    Apply clustering and segmentation techniques (k-means, hierarchical, DBSCAN, Gaussian mixtures) and evaluate stability and usefulness
   </li>
   <li>
    Apply statistics in practice (hypothesis testing, confidence intervals, sampling, experiment design) to support inference and decision-making
   </li>
  </ul>
  <li>
   Deep Learning
  </li>
  <ul>
   <li>
    Build and train deep learning models using PyTorch or TensorFlow/Keras
   </li>
   <li>
    Use best practices for training (regularization, calibration, class imbalance handling, reproducibility, sound train/val/test design)
   </li>
  </ul>
  <li>
   Evaluation, Explainability, and Iteration
  </li>
  <ul>
   <li>
    Choose appropriate metrics (AUC/F1/PR, RMSE/MAE/MAPE, calibration, lift, and business KPIs) and create evaluation reports
   </li>
   <li>
    Perform error analysis and interpretation (feature importance/SHAP, cohort slicing) and iterate based on evidence
   </li>
  </ul>
  <li>
   Productionization &amp; MLOps (Project-Dependent)
  </li>
  <ul>
   <li>
    Package models for deployment (batch scoring pipelines or real-time APIs) and collaborate with engineers on integration
   </li>
   <li>
    Implement practical MLOps: versioning, reproducible training, automated evaluation, monitoring for drift/performance, and retraining plans
   </li>
  </ul>
  <li>
   Documentation &amp; Communication
  </li>
  <ul>
   <li>
    Communicate tradeoffs and recommendations clearly to technical and non-technical stakeholders
   </li>
   <li>
    Create documentation and lightweight demos that make results actionable
    <br/>
   </li>
  </ul>
 </ul>
 Success in This Role Looks Like
 <br/>
 <br/>
 <ul>
  <li>
   You deliver models that perform well and move business metrics (revenue lift, cost reduction, risk reduction, improved forecast accuracy, operational efficiency)
  </li>
  <li>
   Your work is reproducible and production-aware: clear data lineage, robust evaluation, and a credible path to deployment/monitoring
  </li>
  <li>
   Stakeholders trust your judgment in selecting methods and communicating uncertainty honestly
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   3&ndash;8 years of experience in data science, machine learning engineering, or applied ML (mid-to-senior)
  </li>
  <li>
   Strong Python skills for data analysis and modeling (pandas/numpy/scikit-learn or equivalent)
  </li>
  <li>
   Strong SQL skills (joins, window functions, aggregation, performance awareness)
  </li>
  <li>
   Solid foundation in statistics (hypothesis testing, uncertainty, bias/variance, sampling) and practical experimentation mindset
  </li>
  <li>
   Hands-on experience across multiple model types, including:
  </li>
  <ul>
   <li>
    Classification &amp; regression
   </li>
   <li>
    Time series forecasting
   </li>
   <li>
    Clustering/segmentation
   </li>
  </ul>
  <li>
   Experience with deep learning in PyTorch or TensorFlow/Keras
  </li>
  <li>
   Strong problem-solving skills: ability to work with ambiguous goals and messy data
  </li>
  <li>
   Clear communication skills and ability to translate analysis into decisions
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience with Databricks for applied ML (e.g., Spark, Delta Lake, MLflow, Databricks Jobs/Workflows)
  </li>
  <li>
   Experience deploying models to production (APIs, batch pipelines) and maintaining them over time (monitoring, retraining)
  </li>
  <li>
   Experience with orchestration tools (Airflow, Prefect, Dagster) and modern data stacks (Snowflake/BigQuery/Redshift/Databricks)
  </li>
  <li>
   Experience with cloud platforms (AWS/GCP/Azure/IBM) and containerization (Docker)
  </li>
  <li>
   Experience with responsible AI and governance best practices (privacy/PII handling, auditability, access controls)
  </li>
  <li>
   Consulting or client-facing delivery experience
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Certifications (Strong Plus)
  <br/>
  <br/>
 </strong>
 Candidates with at least one relevant certification are especially encouraged to apply:
 <br/>
 <br/>
 <ul>
  <li>
   Cloud certifications: AWS, Google Cloud, Microsoft Azure, or IBM (data/AI/ML tracks)
  </li>
  <li>
   Databricks certifications (Data Scientist, Data Engineer, or related)
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Nice-to-Have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Causal inference experience (e.g., quasi-experimental methods, propensity scores, uplift/heterogeneous treatment effects, experimentation beyond A/B tests)
  </li>
  <li>
   Agentic development experience: designing and evaluating agentic workflows (tool use, planning, memory/state, guardrails) and integrating them into products
  </li>
  <li>
   Deep familiarity with agentic coding tools and workflows for accelerated product development (e.g., AI-assisted IDEs, code agents, automated testing/refactoring, repo-aware assistants), including strong judgment on quality, security, and maintainability
   <br/>
   <br/>
  </li>
 </ul>
 <em>
  <em>
   Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.
   <br/>
   <br/>
  </em>
 </em>
 Important: Immigration Sponsorship Policy
 <br/>
 <br/>
 Fusemachines is unable to proceed with candidates who require any form of work authorization or immigration support from the company. This restriction applies to all types of support, including:
 <br/>
 <br/>
 <ul>
  <li>
   Direct Company Sponsorship: Such as H-1B, J-1, or TN visas
  </li>
  <li>
   Employer of Record: Listing Fusemachines as the immigration employer on any government documentation
  </li>
  <li>
   Written Documentation: Providing letters or other support for any work authorization (e.g., OPT, STEM OPT, CPT)
   <br/>
   <br/>
  </li>
 </ul>
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