data analytics chief scientist

JP Techno Park

<ul><li>JOB DESCRIPTION</li></ul><p>We are seeking a highly skilled Data Scientist along with strong Data Engineering expertise to<br/>join Advance Analytics and Modeling team. The ideal candidate will have a proven ability to<br/>work with diverse datasets, build machine learning models, and deploy scalable solutions.<br/>This role requires proficiency in Python, advanced analytical skills, and experience in<br/>developing machine learning models and dashboards in python. The candidate should<br/>have experience in deploying machine learning models in production using cloud platforms such<br/>as AWS or Azure and workflow orchestration tools like Airflow.</p><p>Key Responsibilities:</p><ul><li>Develop and deploy machine learning models for classification, regression, and</li><li>clustering problems.</li><li>Perform statistical analysis to derive actionable insights from data.</li></ul><ul><li>Design and implement predictive analytics solutions to support business decision-</li></ul><p>making.Docker)translate them into analytical solutions.</p><ul><li>Design, build, and optimize data pipelines using Airflow.</li><li>Ensure data quality, integrity, and availability through robust ETL processes.</li><li>Work on model deployment using Python-based frameworks and containerization (e.g.,</li><li>Create interactive dashboards using Python libraries to visualize data and results.</li><li>Collaborate with cross functional teams to understand business requirements and</li></ul><p>Required Skills &amp; Expertise:</p><p>Technical Skills:</p><ul><li>Proficiency in Python, advanced Python concepts (object-oriented programming,</li><li>multi-threading, etc.), SQL and Excel.</li><li>Hands-on experience with data visualization tools (e.g., Tableau, Power BI) is a</li></ul><p>plus.Analytics and Machine Learning:</p><ul><li>Strong analytical skills and experience in predictive modeling.</li><li>Hands-on experience with machine learning libraries like scikit-learn, TensorFlow</li><li>or PyTorch.</li><li>Ability to work with large datasets and extract meaningful insights to generate</li></ul><p>output</p><ul><li>Ability to work on ad-hoc requests to support business needs and derive</li></ul><p>actionable insightsData Visualization:Streamlit.</p><ul><li>Experience inn creating dashboards using Python libraries like Plotly, Dash, or</li></ul><p>Data Engineering:</p><ul><li>Knowledge of Airflow or similar workflow orchestration tools.</li><li>Expertise in ETL processes and pipeline automation.Model Deployment:</li><li>Familiarity with deploying machine learning models in production using Flask,</li><li>FastAPI, or similar frameworks.</li><li>Experience with containerization and orchestration tools (Docker, Kubernetes.)</li></ul><p>Tools and Platforms:</p><ul><li>Experience with version control tools like Git.</li><li>Familiarity with cloud platforms like AWS, Azure, or GCP is a plus.</li><li>Problem-Solving &amp; Communication: Strong problem-solving skills, with the ability to translate complex analytical findings into clear and actionable recommendations.</li><li>Excellent communication and presentation skills, with experience delivering</li><li>insights to senior stakeholders.Candidate Profile:</li><li>Educational Background: Bachelor&rsquo;s/Master&rsquo;s degree in Analytics, Data Science, Economics, Statistics, Engineering, or a related field.</li><li>Professional Experience: At least 5 years of experience in Data Science and Data</li></ul><p>Engineering.</p><p>Job Type: Full-time</p><p>Pay: &#8377;1,500,000.00 - &#8377;1,800,000.00 per year</p><p>Experience:</p><ul><li>Data Scientist: 10 years (Required)</li><li>Python: 10 years (Required)</li><li>Analytical Data: 10 years (Required)</li><li>PySpark: 10 years (Required)</li><li>SQL: 10 years (Required)</li><li>Excel: 10 years (Required)</li><li>Data Visualization: 10 years (Required)</li><li>Insurance: 10 years (Required)</li><li>Tableau: 10 years (Required)</li><li>Power BI: 10 years (Required)</li><li>Data Engineering: 10 years (Required)</li><li>machine Learning: 10 years (Required)</li><li>ETL: 10 years (Required)</li><li>Automation: 10 years (Required)</li><li>Flask: 10 years (Required)</li></ul><p>Work Location: In person</p>

Lead Analytical Data Scientist

Cushman & Wakefield

<div><p><b>Job Title</b></p>
Principal Data Scientist | Bangalore<p><b>
Job Description Summary</b></p>
The Principal Data Scientist will lead predictive modeling, advanced analytics, and emerging AI initiatives such as GPT, generative AI, and NLP for the Organic Growth Team (OGT). This role involves architecting and deploying predictive and generative AI models, extracting actionable insights, and collaborating closely with stakeholders to drive strategic, data-driven outcomes. The ideal candidate has approximately 10 years of experience in data science and AI, with demonstrated expertise in predictive modeling, machine learning, NLP, generative AI frameworks, and strategic analytics leadership.
<br>
<br>
This role will collaborate closely with the Sales &amp; Pursuits team, internal stakeholders and occasionally global counterparts to build predictive models that drive strategic decision-making and optimize sales performance.
<br>
<br>
While the primary focus will be on the Asia Pacific region, this role may be required to collaborate with other regions including Europe, Middle East and Africa (EMEA) as well as the Americas, with the intent of sharing insights and best-practices.<p><b>
Job Description</b></p><p></p><p><b>
About The Role:</b></p><ul><li><b>
Data Science and AI Roadmap </b>&ndash; Work with leadership to design and evolve the roadmap for Data Science and AI, ensuring alignment with business objectives and emerging technology trends.</li><li><b>
Solution Development &ndash;</b> Lead the design, development, and deployment of predictive models, machine learning algorithms, and generative AI / NLP solutions to identify growth opportunities and inform strategic decision-making.</li><li><b>
Effort Estimation -</b> Provide accurate effort and resource estimations for proposed solutions and prepare quotes for internal stakeholders to assist in decision-making</li><li><b>
Pipeline and Project Management</b> &ndash; Lead a team to deliver data science and AI projects from ideation through implementation, ensuring timely delivery, clear project reporting and measurable business impact</li><li><b>
Stakeholder collaboration</b> &ndash; Work closely with other streams of the OGT (Sales and Pursuits, Data Analytics, Data Architecture and Engineering) to understand business needs and define effective analytical approaches leveraging Data Science and AI</li><li><b>
Team Leadership</b> &ndash; Provide technical mentorship and guidance to junior data scientists and analysts, fostering a culture of continuous learning and technical excellence</li><li><b>
Communication and Storytelling</b> &ndash; Translate complex analytical and AI-driven results into clear, actionable insights and effectively communicate findings to business leaders and stakeholders</li><li><b>
Continuous Improvement</b> &ndash; Drive the continuous improvement of analytical methodologies and data quality processes within the team. Regularly share best practices, lessons learned and foster a culture of continuous improvement</li><li><b>
Knowledge Documentation</b> &ndash; maintain comprehensive documentation of data products, analytics methodologies and insights.
</li></ul><p></p><p><b>About You:</b></p><ul><li>
Expertise in statistical modeling, machine learning techniques, predictive analytics, NLP, and generative AI frameworks (e.g., GPT models).</li><li>
Expert Level Proficiency in programming languages such as Python, R, and SQL.</li><li>
Experience with data visualization tools (e.g., Power BI)</li><li>
Strong understanding of data processing frameworks, ETL pipelines, data warehousing, and data lake concepts.</li><li>
Deep knowledge of deep learning frameworks and libraries (e.g., PyTorch, TensorFlow, HuggingFace).</li><li>
Demonstrated ability to lead complex analytical and AI projects from inception through deployment.</li><li>
Excellent communication and interpersonal skills, with a proven track record of articulating complex analytical and AI concepts clearly to non-technical stakeholders.</li><li>
Familiarity with both unstructured and structured data sources, especially cloud services and platforms (Azure, AWS) and exposure to big data technologies.</li><li>
Proven ability to innovate and develop novel analytical and AI-driven solutions, influencing strategic direction and promoting innovation within the organization.</li><li>
Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.</li><li>
Approximately 10-15 years of professional experience in data science, predictive modeling, AI, NLP, or related fields.</li></ul><p></p><p><b>
Why join Cushman &amp; Wakefield?
</b></p><p></p><p>As one of the leading global real estate services firms transforming the way people work, shop and live working at Cushman &amp; Wakefield means you will benefit from;</p><ul><li>
Being part of a growing global company;</li><li>
Career development and a promote from within culture;</li><li>
An organisation committed to Diversity and Inclusion</li></ul><p></p><p>
We're committed to providing work-life balance for our people in an inclusive, rewarding environment.<br>
We achieve this by providing a flexible and agile work environment by focusing on technology and autonomy to help our people achieve their career ambitions. We focus on career progression and foster a promotion from within culture, leveraging global opportunities to ensure we retain our top talent. We encourage continuous learning and development opportunities to develop personal, professional and technical capabilities, and we reward with a comprehensive employee benefits program.</p><p></p><div><p><b>
We have a vision of the future, where people simply belong.</b></p><p></p><p><i><br>
That's why we support and celebrate inclusive causes, not just on days of recognition throughout the year, but every day. We embrace diversity across race, colour, religion, sex, national origin, sexual orientation, gender identity or persons with disabilities or protected veteran status.
</i></p></div><p><i>We ensure DEI is part of our DNA as a global community - it means we go way beyond than just talking about it - we live it. If you want to live it too, join us.</i></p><br>
<p></p>
INCO: &ldquo;Cushman &amp; Wakefield&rdquo;</div>

Principal Data Scientist | Bangalore

ZEISS Group

<div><div>ZEISS in India</div><div></div><div>
ZEISS in India is headquartered in Bengaluru and present in the fields of Industrial Quality Solutions, Research Microscopy Solutions, Medical Technology, Vision Care and Sports &amp; Cine Optics.</div><div></div><div>
ZEISS India has 3 production facilities, R&amp;D center, Global IT services and about 40 Sales &amp; Service offices in almost all Tier I and Tier II cities in India. With 2200+ employees and continued investments over 25 years in India, ZEISS&rsquo; success story in India is continuing at a rapid pace.</div><div></div><div>
Further information at <div>ZEISS India</div>.</div><div></div><div>
In this role you will:</div><div>
Focus on communication, conceptual, and organizational work</div><ul><li>
Partner with stakeholders to identify, design and evaluate AI solutions by translating complex business challenges into practical ML and GenAI use cases</li><li>
Lead data-driven projects, from requirements analysis to implementation, with a strong focus on business impact</li><li>
Lead and mentor junior data scientists, while clearly communicating complex AI concepts to both technical and non-technical audiences.</li><li>
Drive the topic of GenAI forward together with the team and our GenAI task force &ndash; from employee training to building the GenAI architecture.</li></ul><div>
and hands-on programming</div><ul><li>
Provide practical insights into feasibility of AI use cases by rapid prototyping</li><li>
Experiment with cutting-edge technologies such as Agentic AI, Deep Learning, and Large Language Models (LLMs), while exploring their seamless integration into our existing data products and projects</li></ul><div></div><div>
You have:</div><ul><li>
Preferably Master's degree in a STEM (Science, Technology, Engineering, Mathematics) subject, such as Data Science, Computer Science, Statistics, Mathematics, or a related field.</li><li>
5+ years of experience as a data scientist, ideally in a senior or lead role.</li><li>
Solid expertise in machine learning, including supervised and unsupervised, along with experience in model evaluation, interpretability, and deployment.</li><li>
You are hands-on with deep learning and GenAI, working with transformers, LLMs, diffusion models, and multimodal AI.</li><li>
Fluency in Python and relevant libraries (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow, statsforecast, LangChain)</li><li>
Experience in MCP is a plus</li><li>
You have strong skills in data handling, from preprocessing and feature engineering to advanced analytics</li><li>
Strong organizational and project management skills, with the ability to manage multiple priorities and deadlines</li><li>
Strong communication skills in English, with the ability to explain complex topics clearly.</li><li>
A collaborative mindset, curiosity, and confidence to challenge the status quo.</li></ul><div></div><div>
Your ZEISS Recruiting Team:</div>
Upasana Sinal</div>

Lead Data Scientist – Predictive Analytics / GenAI

Citco

<div><p>Citco Bank is seeking an experienced Data Scientist to lead our growing analytics team. The ideal candidate will combine strong technical expertise, business acumen, and proven management experience to develop and implement sophisticated machine learning models and data-driven solutions. This role will be crucial in driving data-based decision-making across our banking and financial services operations working closely with cross-functional teams to deliver actionable insights and innovative solutions.</p></div>
<br><div><ul><li>Lead the development and implementation of advanced machine learning models and statistical analyses to solve complex business problems
</li><li>Collaborate with business stakeholders to understand requirements and translate them into analytical solutions
</li><li>Manage a team of business intelligence experts
</li><li>Work closely together with the technology teams in implementing new techniques into the Citco Bank environments
</li><li>Develop predictive models for risk assessment, fraud detection, customer behavior analysis or forecasting
</li><li>Create and maintain detailed documentation of methodologies, models, and processes
</li><li>Design and build scalable data pipelines and ETL workflows
</li><li>Present findings and recommendations to senior management and stakeholders
</li><li>Monitor model performance and implement improvements as needed
</li><li>Ensure compliance with banking regulations and data governance policies</li></ul></div>
<br><div><p>Education:
</p><ul><li>Master's degree or Ph.D. in Data Science, Statistics, Computer Science, Mathematics, or related field
</li><li>Professional certifications in relevant technologies or methodologies are a plus
</li></ul><p>Experience:
</p><ul><li>10+ years of experience in data science, with at least 4 years in the banking/financial services sector
</li><li>Proven track record of successfully implemented machine learning models in production
</li><li>Minimum 3 years of experience managing and leading data science teams
</li><li>Demonstrated experience in building and developing high-performing teams
</li></ul><p>Technical Skills:
</p><ul><li>Advanced knowledge of machine learning algorithms and statistical modeling
</li><li>Strong expertise in Python, R, or similar programming languages
</li><li>Proficiency in SQL and experience with big data technologies (Hadoop, Spark, Databricks)
</li><li>Experience with deep learning frameworks
</li><li>Knowledge of cloud platforms (AWS, Azure, or GCP)
</li><li>Expertise in data visualization tools (Tableau, Power BI, Qlik)
</li><li>Strong understanding of version control systems (Git)
</li><li>Experience with MLOps and model deployments
</li></ul><p>Business Skills:
</p><ul><li>Proven people management and leadership abilities
</li><li>Experience in resource planning and team capacity management
</li><li>Excellent problem-solving and analytical thinking abilities
</li><li>Strong communication and presentation skills
</li><li>Ability to translate complex technical concepts to non-technical stakeholders
</li><li>Experience in agile development methodologies
</li><li>Understanding of banking and financial services domain
</li></ul><p>Domain Knowledge:
</p><ul><li>Understanding of risk management, compliance, products and regulatory requirements in banking
</li><li>Knowledge of financial markets and instruments is a plus</li></ul></div>

Sr. Vice President - Data Scientist

JPMorganChase

<div>
 <strong>
  Job Description
  <br/>
  <br/>
 </strong>
 Job Summary:
 <br/>
 <br/>
 J.P. Morgan Compliance, Conduct, and Operational Risk (CCOR) Data Science function is at the forefront of developing innovative AI and ML solutions to enhance risk management and compliance processes. Our team leverages advanced analytics, AI, Machine learning technologies, including Large Language Models (LLMs), to transform how we manage compliance, conduct, and operational risks across the organization.
 <br/>
 <br/>
 Join our CCOR Data Science team as a Lead Data Scientist, where you will play a crucial role in developing AI/ML solutions to enhance compliance and risk management. Your primary responsibilities will include leveraging advance AI / ML techniques, LLMs and Agentic AI to develop and deploy models for various tasks such as anomaly detection, risk assessment, and compliance monitoring. You will work with diverse datasets to improve our risk management processes and ensure regulatory compliance. As part of a leading analytics community, you will have opportunities for skill development and career growth in AI, machine learning, and data science.
 <br/>
 <br/>
 <strong>
  Job Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, deploy, and manage AI/ML models, leverages advance AI/ML techniques, LLMs and Agentic AI for developing compliance and risk management related solution.
  </li>
  <li>
   Conduct research on AI techniques to enhance model performance in the compliance and risk domains.
  </li>
  <li>
   Collaborate with cross-functional teams to identify requirements, develop solutions, and deploy models in the production system.
  </li>
  <li>
   Communicate technical concepts effectively to both technical and non-technical stakeholders.
  </li>
  <li>
   Develop and maintain tools and frameworks for model training, evaluation, and optimization.
  </li>
  <li>
   Analyze and interpret data to evaluate model performance and identify areas for improvement.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Qualifications, Capabilities, And Skills
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Master&rsquo;s degree in quantitative discipline or an MBA with an undergraduate degree in areas such as Computer Science, Statistics, Economics, Mathematics etc. from top tier Universities.
  </li>
  <li>
   Minimum of 8 years of relevant experience in developing AI/ML solutions, with recent exposure to LLMs and Agentic AI.
  </li>
  <li>
   Programming skills in Python, with experience in frameworks like PyTorch or TensorFlow.
  </li>
  <li>
   Thorough knowledge of machine learning concepts, including transformers and language modeling.
  </li>
  <li>
   Experience in data pre-processing, feature engineering, and data analysis.
  </li>
  <li>
   Excellent problem-solving skills and the ability to communicate ideas and results clearly.
  </li>
  <li>
   Familiarity with data structures and algorithms for effective problem-solving in machine learning workflows.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  ABOUT US
  <br/>
  <br/>
 </strong>
 JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world&rsquo;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.
 <br/>
 <br/>
 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&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
 <br/>
 <br/>
 <strong>
  About The Team
  <br/>
  <br/>
 </strong>
 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&rsquo;re setting our businesses, clients, customers and employees up for success.
</div>


Vice President – Data Science / Applied AI ML

Options Clearing Corporation

<div><div>*****THIS POSITION IS NOT ELIGIBLE FOR VISA SPONSORSHIP*****</div><div></div><div><div>
Summary</div><div></div><div>
This role is responsible for expanding OCC&rsquo;s analytics capabilities by developing business-focused data engineering solutions and enterprise data models for our most important data assets. In this role, you will lead the design build of our internal analytics cloud data lake&rsquo;s semantic layer and the maintenance of the supporting ETL processes, with an emphasis on transformation and serving curated data that accelerates the ability of teams across the organization in successfully harnessing these data. You will collaborate with business users and technical teams across the organization to facilitate data-driven decision making by enabling exploration and analysis of historical and near real-time data access using cloud-based tools and technologies. Lastly, you will be responsible for gathering requirements and designing solutions that address the problem at hand, anticipating the yet-to-be-asked questions, and align to the company&rsquo;s security and IT standards.</div><div></div><div>
Responsibilities</div><ul><li>
To perform this job successfully, an individual must be able to perform each primary duty satisfactorily.<br>
<ul><li></li></ul>
Partner with relevant business and technology teams to design and implement new cloud-based semantic layer to accelerate and simplify the analytics development of downstream users that develop quantitative analytics, internal risk apps, and BI dashboards.<br>
<ul><li></li></ul>
Lead business and technology SMEs to develop OCC&rsquo;s business domain model, which will empower communication and reasoning across the firm about the meaning of our core, proprietary data assets and how they generate and relate to each other.<br>
<ul><li></li></ul>
Drive the build, test, and deployment patterns of the semantic layer&rsquo;s virtual and physical data models that simplify complex semi-structured data, eliminate multiple definitions of similar data, create query-friendly datasets, and standardize column naming<br>
<ul><li></li></ul>
Establish and maintain trust in the semantic layer by shaping our DataOps practices of observability, monitoring, and automation of quality checks and ETL pipeline health for proactive system failure detection and incident response, before our users find out.<br>
<ul><li></li></ul>
Maintain user query performance requirements of our semantic layer by optimizing storage and SQL object materialization patterns<br>
<ul><li></li></ul>
Collaborate with Data Governance team and DBAs to design access controls around our analytics warehouse to meet Data Governance needs<br>
<ul><li></li></ul>
Work with upstream data producers to understand how their systems generate data, and how they are subject to change over time to help anticipate and manage schema drift from semantic layer<br>
Business Sensitive<br>
<ul><li></li></ul>
Curate and maintain the company&rsquo;s business domain model documentation<br>
<ul><li></li></ul>
Create documentation to ensure data lineage is traceable and semantic layer components are easily discoverable and useful to business users from the data governance tools.<br>
<ul><li></li></ul>
Invest in your continued learning of on modern data engineering, cloud computing, options trading industry, and financial risk management, with an eye towards improving maintainability, reliability, and utility of our analytics infrastructure</li></ul><div></div><div>
Supervisory Responsibilities</div><div>
None</div><div></div><div>
Are the essential duties of this job required to be performed in an OCC office location? No</div><div></div><div>
Qualifications &amp; Experience</div><ul><li>
The requirements listed are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the primary functions.<br>
<ul><li></li></ul>
[Required] Ability to collaborate with multiple partners (e.g. Business Users, Data and Solution Architects, Data Governance and IT teams - Data Platform Team, Systems &amp; Infrastructure, Security, DevOps, Networking) to craft solutions that align business goals with internal processes, security, and delivery standards in mind.<br>
<ul><li></li></ul>
[Required] Past experiences building data products, data warehouses, databases, and other analytics systems depended on by other employees or customers<br>
<ul><li></li></ul>
[Required] Ability to communicate technical concepts to audiences and ask pressing questions of people with varying levels of technical background, and synthesize non-technical requests into a technical specification<br>
<ul><li></li></ul>
[Required] High attention to detail, tradeoffs, and an ability to think structurally about a solution<br>
<ul><li></li></ul>
[Required] Strong presentation and communication skills, including ability to clearly explain deliverables/results to non-technical audiences<br>
<ul><li></li></ul>
[Required] Experience working within an agile environment<br>
<ul><li></li></ul>
[Preferred] Subject matter experience working in the financial trading industry or a similar domain</li></ul><div></div><div>
Technical Skills &amp; Background</div><div>
Demonstrated proficiency in:</div><div></div><div>
[Required] Experience implementing and maintaining cloud-based data warehouses or data lakes and maintaining a semantic layer that meets the needs of business users</div><ul><li>[Preferred] Familiarity with data modeling design concepts such as 3rd-normal form versus denormalized data modeling concepts like star-schema or data vault</li><li>[Required] Ability to write and optimize complex analytical (SELECT) SQL queries and DDL queries, with an understanding of SQL optimization strategies</li><li>[Required] Strong presentation and communication skills, including ability to clearly explain deliverables/results to non-technical audiences</li><li>[Required] Ability to write and manage python projects for custom data pipeline code (virtual environments, functional programming vs. OOP, unit testing)</li><li>[Required] Experience with a source code version control repository system, branch management patterns, pull requests, with a tool such as git and Github</li><li>[Required] Experience working with a linux shell and with container technology, such as docker or podman for portable code distribution and execution</li><li>[Preferred] Experience with transformation or semantic layer frameworks, such as dbt or Cube</li><li>[Preferred] Experience with batch orchestration tools such as Apache Airflow</li><li>[Preferred] Experience with data lake architectures, their open technology components and purpose in modern cloud data stacks for analytics, such as Apache Parquet, Apache Iceberg, and distributed or columnar optimized query engines, such as Trino or duckdb.</li><li>[Preferred] Experience with PAM platforms, such as CyberArk or Hashi Vault</li><li>[Preferred] Experience integrating code with CI/CD tools, like Jenkins, JFrog Artifactory</li><li>[Preferred] Understanding of applied statistics and hands-on experience applying these concepts</li><li>[Preferred] Experience with visualization/reporting tools, such as Tableau or Power BI</li><li>[Preferred] Experience with self-service ETL tools, such as AWS Glue or Alteryx</li></ul><div></div><div>
Education &amp; OR Experience</div><ul><li>
[Required] Bachelor's degree in quantitative discipline (e.g., Statistics, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent professional experience<br>
<ul><li></li></ul>
[Preferred] Master's degree<br>
<ul><li></li></ul>
[Required] 10+ years of experience as a data engineer, data modeler, or data scientist<br>
<ul><li></li></ul>
[Preferred] Work experience in the global financial derivatives trading industry</li></ul></div><div></div><div>
Certificates or Licenses:</div><div></div><div>
[Preferred] Cloud platform certification<br>
<br>
[Preferred] Data Engineering skills certification</div><div></div><div>
About Us</div><div>
The Options Clearing Corporation (OCC) is the world's largest equity derivatives clearing organization. Founded in 1973, OCC is dedicated to promoting stability and market integrity by delivering clearing and settlement services for options, futures and securities lending transactions. As a Systemically Important Financial Market Utility (SIFMU), OCC operates under the jurisdiction of the U.S. Securities and Exchange Commission (SEC), the U.S. Commodity Futures Trading Commission (CFTC), and the Board of Governors of the Federal Reserve System. OCC has more than 100 clearing members and provides central counterparty (CCP) clearing and settlement services to 19 exchanges and trading platforms. More information about OCC is available at www.theocc.com.</div><div></div><div>
Benefits</div><div>
A highly collaborative and supportive environment developed to encourage work-life balance and employee wellness. Some of these components include:</div><ul><li>
A hybrid work environment, up to 2 days per week of remote work</li><li>
Tuition Reimbursement to support your continued education</li><li>
Student Loan Repayment Assistance</li><li>
Technology Stipend allowing you to use the device of your choice to connect to our network while working remotely</li><li>
Generous PTO and Parental leave</li><li>
401k Employer Match</li><li>
Competitive health benefits including medical, dental and vision</li></ul><div></div><div>
Visit <div>https://www.theocc.com/careers/thriving-together</div> for more information.</div><div></div><div>
Compensation</div><ul><li>
The salary range listed for any given position is exclusive of fringe benefits and potential bonuses. If hired at OCC, your final base salary compensation will be determined by factors such as skills, experience and/or education.</li><li>
In addition, we believe in the importance of pay equity and consider internal equity of our current team members as part of any final offer.</li><li>
We typically do not hire at the maximum of the range in order to allow for future and continued salary growth. We also offer a substantial benefits package as noted on <div>www.theocc.com/careers</div></li><li>
All employees may be eligible for a discretionary bonus. Discretionary bonuses are based on various factors, including, but not limited to, company and individual performance and are not guaranteed.</li></ul><div></div><div>
Salary Range</div>
$156,600.00 - $263,200.00<div></div><div>
Incentive Range</div>
23% to 30%<div></div><div>
This position is eligible for an annual discretionary incentive compensation award, for which the target range is listed above (see Incentive Range). The amount of such award, if any, will be based on various factors, including without limitation, both individual and company performance.</div><div></div><div>
Step 1<br>
When you find a position you're interested in, click the 'Apply' button. Please complete the application and attach your resume.</div><div></div><div>
Step 2<br>
You will receive an email notification to confirm that we've received your application.</div><div></div><div>
Step 3<br>
If you are called in for an interview, a representative from OCC will contact you to set up a date, time, and location.</div><div></div><div>
For more information about <div>OCC</div>, please click <div>here</div>.</div><div></div><div>
OCC is an Equal Opportunity Employer</div></div>

Principal, Data Analytics Engineering

Salla

<div>
 Protect millions of buyers and sellers as our Senior Data Scientist for Integrity &amp; Trust. You'll lead building the AI defense systems that detect fraud, eliminate counterfeit products, and maintain marketplace quality across our platform. In MENA's high-COD environment (75% of transactions), trust is everything. Your models will be the difference between platform growth and reputation damage.
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  Responsibilities
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   Build and deploy supervised and unsupervised ML models for policy violation detection, counterfeit detection, and fraud detection
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   Build and grow the Integrity, Safety &amp; Trust pod, mentor applied data scientists and deliver end-to-end projects with measurable business outcomes
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   Design feature pipelines that leverage product text, images, seller behavior, and transaction data
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   Apply NLP models for text classification, entity extraction, and multi-lingual moderation (Arabic + English)
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   Utilize multimodal architectures (CLIP, ViT + BERT) for image-text cross-validation
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   Develop graph-based and anomaly detection models to identify coordinated or suspicious merchant activity
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   Collaborate with product, legal, and operations teams to define integrity policies and feedback loops
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   Implement dashboards and monitoring for real-time detection and escalation (e.g., Elastic, Grafana)
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   Optimize model precision/recall tradeoffs based on enforcement and user experience goals
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   Familiarity with graph learning, anomaly detection, and multimodal data pipelines
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  Requirements
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   Bachelor's or Master's degree in Computer Science, Data Science, or a related field
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   5+ years of experience in applied ML, with at least 2+ years focused on Trust &amp; Safety, Integrity, or Fraud Detection systems
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   Experience with multi-modal text-image modeling (e.g., OCR, CLIP/ViT, layout analysis), taxonomy or attribute extraction, policy classification, and Arabic/English content moderation
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   Strong proficiency in Python, SQL, and ML libraries such as PyTorch, Transformers, Scikit-learn, and OpenCV
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   Experience developing streaming or near-real-time detection systems (Kafka, Redis Streams, or equivalent)
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   Knowledge of e-commerce ecosystems, product policy enforcement, and counterfeit or low-quality detection is a plus
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   Proven experience building or growing a team of applied data scientists and delivering end-to-end projects with measurable business outcomes
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   Excellent analytical reasoning, communication, and cross-functional collaboration skills; able to balance enforcement precision with business impact
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  Benefits
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   Medical Health Insurance
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   Performance Bonus
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   Others
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Lead Data Scientist - Integrity & Safety

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