machine learning manager

Eaton

<div><div><div><div><h2 class="jobSectionHeader"><b>What you&rsquo;ll do:</b></h2>
</div><div><div>
Job Responsibilities<br>
The Manager will be responsible for:<br>
<ul><li>Lead and manage a team of Engineers to deploy and monitor machine learning models in production.</li><li>Working with data engineers for designing data engineering pipelines and performs robust ETL processes to ensure reliable, high‑quality data for analytics and ML workloads.</li><li>Collaborate with cross-functional teams, including data science, engineering, and operations, to understand business requirements and translate them into scalable ML solutions.</li><li>Architect and implement end-to-end machine learning pipelines for model training, testing, deployment, and monitoring.</li><li>Establish best practices and standards for model versioning, deployment, and monitoring to ensure reliability, scalability, and performance.</li><li>Implement automated processes for model training, hyperparameter tuning, and model evaluation using tools such as Weight and Biases, MLflow, Kubeflow, or similar.</li><li>Design and implement infrastructure for scalable and efficient model serving and inference, leveraging technologies such as Kubernetes, Docker, and serverless computing.</li><li>Develop and maintain monitoring and alerting systems to detect model drift, performance degradation, and other issues in production.</li><li>Provide technical leadership and mentorship to team members, fostering their professional growth and development.</li><li>Stay current with emerging technologies and industry trends in machine learning engineering, and evaluate their potential impact on our processes and infrastructure.</li><li>Collaborate with product management to define requirements and priorities for machine learning model deployments and validation, ensuring alignment with business goals and objectives.</li><li>Implement monitoring and logging solutions to track model performance metrics, resource utilization, and system health, enabling proactive issue detection and resolution.</li><li>Lead efforts to optimize resource utilization and cost-effectiveness of machine learning infrastructure, including compute resources, storage, and data transfer.</li><li>Stay abreast of advancements in machine learning technologies, evaluating their applicability and potential impact on our AI Operations strategy and roadmap.</li><li>Foster a culture of innovation, collaboration, and continuous improvement within the AI Operations team, encouraging experimentation and learning from failures.</li></ul></div></div></div><div><div><h2 class="jobSectionHeader"><b>
Qualifications:</b></h2>
</div><div><ul><li>B.tech / M Tech in Computer Science, Electronics or related fields</li><li>
8 Years +</li></ul></div></div><div><div><h2 class="jobSectionHeader"><b>
Skills:</b></h2></div><p></p><div><br>
<ul><li>
Machine Learning, Software Development</li><li>
Research and development, Technology strategy, Global Project Management, Team Management, Mentoring, Risk Management.</li><li>
Desired Skills :<br>
<ul><li>Masters or Bachelor's degree in Computer Science, Engineering, or related field</li><li>8+ years of experience in software engineering, data engineering, or related roles, with at least 2 years in a managerial or leadership role.</li><li>Experience in Designs and maintains scalable data engineering pipelines and performs robust ETL processes to ensure reliable, high‑quality data for analytics and ML workloads</li><li>Previous experience in a leadership or management role, with a track record of successfully leading technical teams and delivering high-impact projects.</li><li>Experience with version control systems (e.g., Git) and collaboration tools (e.g., GitHub, GitLab) for managing code repositories and facilitating team collaboration.</li><li>Familiarity with infrastructure as code (IaC) tools such as Terraform or CloudFormation for provisioning and managing cloud resources.</li><li>Knowledge of software development methodologies (e.g., Agile, DevOps) and best practices for building scalable and reliable software systems.</li><li>Ability to effectively communicate technical concepts and solutions to non-technical stakeholders, including executives, product managers, and business users.</li><li>Strong proficiency in Python, JAVA and related IDEs</li><li>Awareness of machine learning concepts, algorithms, and frameworks (e.g. TensorFlow, PyTorch, sci-kit-learn).</li><li>Experience with cloud platforms and services (e.g., Azure, AWS, GCP) for building and deploying machine learning applications.</li><li>Proficiency in containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes).</li><li>Hands-on experience with MLOps tools and platforms such as Weight and Biase, MLflow, Kubeflow, TFX, or similar.</li><li>Experience in DevOps and DevSecOps tools and practices</li><li>Strong problem-solving skills and ability to troubleshoot complex issues in production environments.</li><li>Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams.</li></ul></li></ul></div></div></div></div>

Engineering Manager - Machine Learning

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability &amp; fulfilment, buying experience and post-buying experience (product quality and customer returns).<br>
<br>
As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and visual), supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, product similarity, using GenAI, LLMs, NLP and Computer Vision.<br>
<br>
Key job responsibilities<br>
As an Applied Science Manager, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will Lead scientists on the team and oversee research and development projects at various stages ranging from initial exploration to deployment into production systems. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will create the environment in the team to file for patents and/or publish research work where opportunities arise. You will impact the large product strategy, identifies new business opportunities and provides strategic direction to the team.</p><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>Knowledge of ML, NLP, Information Retrieval and Analytics</li><li>Master's degree in Computer Science, Statistics, Electrical Engineering, or Mathematics with specialization in specialization in Machine Learning, statistical modeling, or Deep learning.</li><li>5+ years of working experience in solving machine learning problems and deploying science solutions for large-scale applications</li><li>2+ years of experience leading a team of scientists and engineers Knowledge of programming languages such as C/C++, Python, Java</li><li>Excellent written and verbal communication skills</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience building machine learning models or developing algorithms for business application</li><li>Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers</li></ul><br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.</div>

Manager, Applied Science, RBS Tech

Alexion Pharmaceuticals

<div><div><div>Location: Bengaluru, India
</div><div>Job reference: R-246280</div>
<div>Date posted: 02/23/2026</div>
</div><div><h1 class="jobSectionHeader"><b>Job Title: Manager, RDU IT &ndash; Data Science</b></h1><p><b>
Introduction to role:</b><br>
Are you ready to lead the charge in developing cutting-edge Generative AI solutions? As a Manager, RDU IT &ndash; Data Science, you'll be at the forefront of innovation, reporting directly to the IT Director of Data Science within the Alexion IT RDU organization. Your mission? To craft and deploy AI models that tackle our most pressing business challenges. Dive into the world of Machine Learning and Generative AI, and help us scale production-ready models that make a real impact!</p><div><b>
Accountabilities:</b><br>
<ul><li>Lead the development and refinement of Generative AI systems and applications using state-of-the-art models to solve complex business problems.</li><li>Contribute to the development and maintenance of MLOps infrastructure and tools for Machine Learning and Generative AI models.</li><li>Participate in the full lifecycle development of Generative AI agents, ensuring meaningful interaction with users or environments.</li><li>Support the integration of pre-trained Generative AI models into custom applications for new functionalities.</li><li>Collaborate with senior engineers to design interactive systems using Generative AI for dynamic content or decision support.</li><li>Contribute to building and maintaining infrastructure for running Generative AI applications.</li><li>Aid in implementing user interfaces or API endpoints for seamless interaction with Generative AI functionalities.</li><li>Assist with data pipelines and preprocessing steps for feeding Generative AI models with appropriate data.</li><li>Help monitor the operational health of Generative AI applications in production, identifying areas for improvement or optimization.</li><li>Contribute to developing assets, frameworks, and reusable components for Generative AI, Machine Learning, and MLOps practices.</li><li>Engage with stakeholders to gather feedback and iteratively improve upon Generative AI applications' features and capabilities.</li><li>Support the integration of Generative AI models within the Machine Learning ecosystem, ensuring ethical use and business relevance.</li><li>Assist with monitoring and governance of Generative AI models to align with evolving business and regulatory requirements.</li></ul></div><div><b>
Essential Skills/Experience:</b><br>
<ul><li>Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field</li><li>3+ years of experience in Machine Learning, data science, or software development</li><li>Familiarity with ML Engineering concepts and tools, including Docker/containerization, and basic model upkeep</li><li>Exposure to CICD practices and familiarity with tools such as GitHub Actions, Jenkins, or Bitbucket pipelines</li><li>Experience with Python and familiarity with ML libraries such as Tensorflow, Keras, or PyTorch</li><li>Experience with cloud computing platforms, such as AWS, Azure or GCP</li><li>Understanding of software engineering principles and exposure to agile methodologies</li><li>Good communication and collaboration skills, with enthusiasm for working in a cross-functional team environment</li><li>Proactive and eager to learn with strong analytical and problem-solving skills</li></ul></div><div>
Desirable Skills/Experience:<br>
<ul><li>Experience in the pharmaceutical industry or related fields</li><li>Master's degree in a related field or ongoing education towards an advanced degree</li><li>Strong knowledge of AI techniques and tools, including NLP, optimization, and deep learning</li></ul></div><p>
When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.</p><p>
At AstraZeneca, you'll find a vibrant environment where innovation thrives. Our entrepreneurial spirit combined with global resources allows us to make significant strides in healthcare. We are committed to supporting your career growth while making a difference in patients' lives. With a rapidly expanding portfolio and a culture that encourages exploration and learning, you'll be empowered to define your career path while contributing to groundbreaking advancements.</p><p>
Ready to take on this exciting challenge? Apply now and become part of our dynamic team!</p><p><b>
Date Posted</b></p>
23-Feb-2026<p><b>
Closing Date</b></p>
13-Mar-2026<p>
Alexion is proud to be an Equal Employment Opportunity and Affirmative Action employer. We are committed to fostering a culture of belonging where every single person can belong because of their uniqueness. The Company will not make decisions about employment, training, compensation, promotion, and other terms and conditions of employment based on race, color, religion, creed or lack thereof, sex, sexual orientation, age, ancestry, national origin, ethnicity, citizenship status, marital status, pregnancy, (including childbirth, breastfeeding, or related medical conditions), parental status (including adoption or surrogacy), military status, protected veteran status, disability, medical condition, gender identity or expression, genetic information, mental illness or other characteristics protected by law. Alexion provides reasonable accommodations to meet the needs of candidates and employees. To begin an interactive dialogue with Alexion regarding an accommodation, please contact accommodations@Alexion.com. Alexion participates in E-Verify.</p></div></div><p></p>

Manager, RDU IT – Data Science

Autodesk

<div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div>Job Requisition ID #</div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><div></div>
26WD95896<div></div><div>
Position Overview</div><div></div><div>
We are looking for an ML Engineering Manager to lead and grow the machine learning team within Autodesk&rsquo;s Growth and Experience Technology (GET) organization. Autodesk builds products used by millions of designers, engineers, and creators around the world. Over the next five years, AI will play a defining role in how our customers discover, purchase, and experience our products. Building and executing a strong applied AI strategy within GET is critical to that ambition.</div><div></div><div>
As an ML Engineering Manager, you will have the autonomy and ownership to shape how machine learning drives measurable business impact across Autodesk&rsquo;s go-to-market ecosystem. You will build and scale a high-performing team, define applied ML roadmaps, and lead the delivery of systems that influence real customer experiences at global scale. This is a player&ndash;coach role in a strategically important and fast-evolving area. You will remain technically engaged while growing a team from the ground up&mdash;establishing standards, shaping culture, and building durable ML capabilities that will expand over time.</div><div></div><div>
If you are excited about building teams, owning outcomes, and helping define how AI accelerates Autodesk&rsquo;s next chapter of growth, this role offers both the scope and the runway to do it. Autodesk follows a hybrid work model. You may work remotely or from an Autodesk office, with periodic travel as business needs require.</div><div></div><div>
Responsibilities</div><div></div><div>
Team Leadership &amp; Growth</div><ul><li>Hire, onboard, and develop a high-performing team of machine learning engineers</li><li>Provide clear direction, regular coaching, and performance feedback to support career growth</li><li>Foster a collaborative, inclusive, and high-performance culture that is ambitious, disciplined, and sustainable</li><li>Build strong hiring pipelines and drive the long-term growth and composition of the team</li></ul><div>
Applied ML Strategy &amp; Impact</div><ul><li>Define and evolve the applied ML roadmap for the team, aligning technical priorities with business outcomes</li><li>Own the end-to-end success of ML initiatives&mdash;from understanding customer and business needs to delivering measurable production impact</li><li>Establish a high technical bar across experimentation, evaluation, and production readiness</li><li>Guide architectural decisions and ensure systems are scalable, maintainable, and reliable</li><li>Make pragmatic trade-offs between innovation speed and system reliability to deliver sustainable impact</li><li>Hold the team accountable for translating ML investments into measurable improvements in customer experience and business performance</li><li>Remain technically engaged&mdash;contributing through design reviews, technical deep dives, and hands-on problem solving when needed</li></ul><div>
Cross-Functional Leadership</div><ul><li>Partner closely with product, design, and engineering leaders to align ML initiatives with go-to-market and growth strategy</li><li>Advocate for experimentation rigor and evidence-based decision-making</li><li>Represent and advocate for the team within the broader GET organization and Autodesk AI ecosystem</li></ul><div></div><div>
Minimum Qualifications</div><div></div><ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, Statistics, or a related field (or equivalent practical experience)</li><li>8+ years of experience building and deploying production-grade software or machine learning systems</li><li>2+ years of experience leading or managing engineering teams</li><li>Strong understanding of the end-to-end ML lifecycle and production considerations</li><li>Proven track record of delivering data-driven systems that drive measurable impact</li><li>Solid software engineering fundamentals and system design skills</li><li>Demonstrated ability to lead cross-functional initiatives in product-driven environments</li></ul><div></div><div>
Preferred Qualifications</div><div></div><ul><li>Experience leading applied ML efforts in areas such as personalization, ranking, search, or growth-focused systems</li><li>Experience operating in customer-facing, go-to-market, or product-led environments</li><li>Experience scaling teams and building durable engineering processes</li><li>Familiarity with modern ML tooling and cloud-based production environments</li><li>Strong written and verbal communication skills, with the ability to explain technical trade-offs clearly</li></ul><div></div><div>
#LI-AK1</div><div></div><div>
Learn More</div><div></div><div>
About Autodesk</div><div>
Welcome to Autodesk! Amazing things are created every day with our software &ndash; from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.</div><div></div><div>
We take great pride in our culture here at Autodesk &ndash; it&rsquo;s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.</div><div></div><div>
When you&rsquo;re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!</div><div></div><div>
Salary transparency</div>
Salary is one part of Autodesk&rsquo;s competitive compensation package. Offers are based on the candidate&rsquo;s experience and geographic location. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.<div></div><div>
Diversity &amp; Belonging<br>
We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: <div>https://www.autodesk.com/company/diversity-and-belonging</div></div><div></div><div>
Are you an existing contractor or consultant with Autodesk?</div><div>
Please search for open jobs and apply internally (not on this external site).</div></div>

Engineering Manager (ML)

Nissan Motor Corporation

<div>
 <p>
  <strong>
   Responsibilities:
  </strong>
 </p>
 <ul>
  <li>
   Lead and manage data science teams, overseeing the development and deployment of machine learning models and advanced analytics solutions.
  </li>
  <li>
   Define and execute data strategies aligned with business objectives, ensuring actionable insights drive decision-making.
  </li>
  <li>
   Collaborate with cross-functional teams, including engineering, product, and business stakeholders, to identify and solve complex data-related challenges.
  </li>
  <li>
   Ensure data integrity, governance, and security while optimizing data pipelines and infrastructure for scalability.
  </li>
  <li>
   Mentor and develop data scientists, providing technical guidance, performance feedback, and career development support.
  </li>
  <li>
   Stay updated on emerging trends, technologies, and best practices in data science and artificial intelligence (AI).
  </li>
  <li>
   Communicate findings effectively to both technical and non-technical stakeholders, translating insights into business impact.
  </li>
 </ul>
 <p>
  <strong>
   Key Competencies:
  </strong>
 </p>
 <ul>
  <li>
   Strong problem-solving and analytical thinking skills to interpret complex data and drive insights.
  </li>
  <li>
   Leadership and people management abilities to guide and grow a high-performing data science team.
  </li>
  <li>
   Business acumen to align data science initiatives with organizational goals and drive measurable value.
  </li>
  <li>
   Effective communication skills for conveying technical concepts to diverse audiences.
  </li>
  <li>
   Decision-making capabilities based on data-driven approaches.
  </li>
 </ul>
 <p>
  <strong>
   Technical Skills:
  </strong>
 </p>
 <ul>
  <li>
   Proficiency in programming languages such as Python, R, or SQL.
  </li>
  <li>
   Expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-Learn).
  </li>
  <li>
   Experience with big data technologies (Spark) and cloud platforms (
   <strong>
    AWS/
   </strong>
   Azure/ GCP).
  </li>
  <li>
   Strong understanding of statistical modeling, predictive analytics, and deep learning.
  </li>
  <li>
   Experience with data visualization tools (Quicksight, Power BI, Matplotlib, Seaborn, Streamlit/Dash).
  </li>
  <li>
   GenAI: Experience with GenAI APIs, LLMs, Vectorization, Agentic AI and prompt engineering for domain-specific solutions
  </li>
  <li>
   MLOps: Ability to build reusable model pipelines and manage deployments using MLflow and Docker
  </li>
 </ul>
 <p>
  <strong>
   Behavioural Competencies:
  </strong>
 </p>
 <ul>
  <li>
   Adaptability: Ability to pivot strategies based on evolving business needs and technological advancements.
  </li>
  <li>
   Learning Agility: Continuous learning mindset to keep up with emerging data science trends and methodologies.
  </li>
  <li>
   Teamwork: Collaborative approach to working with cross-functional teams, fostering knowledge sharing and innovation.
  </li>
 </ul>
 <p>
  <strong>
   Certifications (Optional):
  </strong>
 </p>
 <ul>
  <li>
   Certified Data Scientist (CDS) &ndash; DASCA
  </li>
  <li>
   AWS Certified Machine Learning &ndash; Specialty
  </li>
  <li>
   Microsoft Certified: Azure AI Engineer Associate
  </li>
  <li>
   Coursera/edX Data Science Specializations (e.g., IBM, Stanford, Harvard)
  </li>
  <li>
   Data Engineering Certifications
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   <br/>
   <br/>
   Location : Trivandrum Kerala Ind
  </strong>
 </p>
 <p>
  <br/>
 </p>
 ia
</div>


Data Science Manager

Citi

<div><p><b>Job Description:</b></p><p>
Citi Analytics &amp; Information Management (AIM) team is a global community that objectively connects and analyzes information to create actionable intelligence for our business leaders. It identifies fact-based opportunities for revenue growth and expense reduction in partnership with the businesses. The role of C14 (people manager) having 10+ data scientists reporting to him/her is a part of AIM Financial Crimes Data Analytics and Intelligence (FCDAI) team based in Gurugram and reporting into the Director/Managing Director, AIM. The primary area of focus for this position will be to lead a team of data scientists responsible for working on various tools and technologies for successful development and implementation of Machine learning (ML) /AI/Gen AI models on different platforms, design, develop and deploy generative AI based solutions for AML Transaction monitoring. The person will lead and manage the FCDAI team within AIM, recruit staff, lead professional development and build a high performing team.</p><p></p><p><b>
Job Description Summary:</b></p><ul><li>
Act as Strategic Leader: Incumbents would be primarily responsible for supporting Business Execution activities for Independent Compliance Risk Management (ICRM) AML organization, implement analytical solutions</li><li>
Maintain an industry leading knowledge of the tools, systems, and processes available for best-in-class AML Detection and Monitoring</li><li>
Lead as SME in the area of ML/AI/Gen AI. The person should have strong AI and ML concepts and understand Pros and Cons of AI/ML algorithms for better model selection. Articulate complex AI and ML concepts in a clear manner to diverse audiences including business partners and peers. Stay abreast of the latest advancements, trends and research in AI and ML space. Knowledge of domain-specific NLP applications and use case across various business problems.</li><li>
Lead a team of data scientists with primary responsibility of working on various tools and technologies for successful development and implementation of ML /AI/Gen AI models on different platforms. Provide technical leadership, mentorship, and guidance to a team of model developers. Ensuring 100% execution accuracy.</li><li>
Must be able to provide thought leadership for all data solutions that include designing, developing, and implementing Machine Learning/AI/Gen AI solutions that meet and exceed expectations. Extensive knowledge of code and execute the current state of art ML/AI/Gen AI algorithms and Generative AI across different coding platform.</li><li>
Have extensively worked on advanced programming language &amp; databases (SQL, NoSQL, Teradata, etc.), Python (NumPy, Pandas, etc.), bigdata (Hue, Impala, Ozzie, etc.) and Spark. Communicate complex analytical concepts and results to both technical and non-technical audiences.</li><li>
Establish governance frameworks for model development, deployment, and monitoring to meet MRM and Fair Lending guidelines. Continuously evaluate and improve model monitoring &amp; governance processes to adapt to changing business needs and emerging risks. Strong understanding of MRM guidelines for ML/AI/Gen AI model approvals and ongoing model validation</li><li>
Understand the complexities of data analysis, machine learning and model development to guide team effectively. Overseeing the end-to-end model development lifecycle from data collection and preprocessing to model building, validation, and deployment. Ensure models are developed and deployed in timely manner with high quality and no errors. Strong collaboration among multidisciplinary teams to drive innovation.</li><li>
This role is a people manager role. The role requires leading 10+ data scientists, some of them could be manager of managers, manage their career progression, conflict management, performance management, provide coaching, mentorship, and technical guidance.</li></ul><p><b>
Knowledge and Experience:</b></p><ul><li>
Minimum 15+ years of analytics experience in core model development using ML/AI/Gen AI techniques. Sound knowledge of model development stages and industry best practices in real time deployment with good understanding of pros and cons of different modelling techniques. Strong understanding of current state of the art ML/AI/Gen AI algorithms. Recommend appropriate ML/AI/Gen AI algorithms for business solutioning.</li><li>
Prior experience in AML domain, Mantas, or any other AML Transaction Monitoring systems will be preferred.</li><li>
Strong coding skill with experience in Bigdata environments, intellectual curiosity to stay abreast of technological and data sciences advances. Strong knowledge of the pros, cons, and usage of various ML / DL applications (such as Keras, TensorFlow, Python Scikit, etc.). Strong knowledge of Python, SQL, and Big Data</li><li>
Bachelor&rsquo;s or master&rsquo;s degree in computer science, Data Science, Machine Learning, or a related field. A Ph.D. is a plus.</li><li>
Model execution and governance experience in any domain will be preferable.</li><li>
Proven track record of building and deploying generative models-based solutions in production environments. Proficient in proactive risk mitigation, managing project pipelines to ensure prioritization and required resourcing mix.</li><li>
At least 8 years of people management experience</li><li>
Consistently sets high performance standards with right mentorship &amp; coaching interventions for team. Ownership &amp; accountability of career progression, performance management, IDP and conflict management. Retain talent, manage attrition, and career mobility.</li><li>
Successful candidate will have a demonstrable analytics problem solving and can deliver projects in a challenging environment.</li><li>
Excellent verbal and written communication skills. Communicates seamlessly across team members / stakeholders / cross-functional teams.</li><li>
Strong capability to influence business outcomes / decisions in collaboration with AIM leadership &amp; business stakeholders. Demonstrate thought leadership in partner meetings while leading from the front to drive innovative solutions with excellent stakeholder management.</li><li>
Strong coordination and project management skills; must be able to define business requirements and create robust technical and process documentation to support activities. Identify right skillset requirement for business needs, effective utilization of analytics resources.</li><li>
Ability in strategic thinking and the ability to frame business problems. Excellent analytical, technical, and/or statistical skills with proven ability to translate large volumes of data. An influencer who communicates clearly and frequently to both technical analysts and non-technical business leaders. Intellectually curious, consistently seeking and developing new opportunities.</li></ul><p></p><p>
-</p><p><b>
Job Family Group:
</b></p>Decision Management<p>
-</p><p><b>
Job Family:</b></p>
Specialized Analytics (Data Science/Computational Statistics)<p>
-</p><p><b>
Time Type:</b></p>
Full time<p>
-</p><p><b>
Most Relevant Skills
</b></p>Please see the requirements listed above.<p>
-</p><p><b>
Other Relevant Skills
</b></p>For complementary skills, please see above and/or contact the recruiter.<p>
-</p><p><i>
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.</i></p><p></p><p><i><br>
If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review </i><i>Accessibility at Citi</i><i>.</i><br>
<br>
<i>View Citi&rsquo;s </i><i>EEO Policy Statement</i><i> and the </i><i>Know Your Rights</i><i> poster.</i></p></div>

Financial Crimes Data Analytics & Intelligence Lead-Senior Vice President

Bluevine

<div><div><p><b>About Bluevine</b></p>
<p>
Bluevine is the largest small business banking platform in the U.S., redefining how entrepreneurs manage their money. We create modern financial solutions, from checking and lending to payments and beyond, designed to help small business owners grow, thrive, and take control of their financial future. Our best-in-class technology, advanced security, and deep understanding of the small business community give our customers the confidence to focus on what they do best.</p>
<p>
Since 2013, we've supported more than 750,000 small businesses nationwide. Backed by leading investors like Lightspeed Venture Partners, Menlo Ventures, 83North, and Citi Ventures, our 500+ person global team shares one mission: to give small businesses the financial tools they need to succeed.</p>
<p>
We're innovators driven by big ideas, collaboration, and real impact. Here, you'll have the freedom to take ownership, grow your career, and make a difference for small business owners across America. Ready to shape what's next?</p></div><p><b><i>
This is a hybrid role</i></b><b><i>. </i></b>At Bluevine, we pride ourselves on our collaborative culture, which we believe is best maintained through in-person interactions and a vibrant office environment. All of our offices have reopened in accordance with local guidelines, and are following a hybrid model. In-office days will be determined by location and discipline.</p>
<p><b>
About the Role:</b></p>
<p>
We are establishing a pioneering data science team in India and are seeking a highly skilled Data Science Manager to drive our efforts. In this role, you will lead a team of data scientists, guiding their work while also remaining hands-on with advanced data science tasks. You will play a crucial role in developing and implementing sophisticated models, coordinating with the group lead, and ensuring alignment with our strategic goals.</p>
<p><b>
Key Responsibilities:</b></p>
<ul>
<li><b>Team Leadership &amp; Development:</b> Lead and mentor a team of 2 individual contributors (ICs), providing guidance on project execution, technical challenges, and professional growth. Foster a collaborative and innovative team environment.</li>
<li><b>Hands-on Modeling &amp; Analytics:</b> Apply your expertise in advanced statistical, machine learning, and predictive modeling techniques to design, build, and improve decision-making systems. Set the standard for technical excellence within the team.</li>
<li><b>Project Management:</b> Manage and oversee data science projects from concept to deployment, ensuring timely delivery of high-quality solutions. Allocate resources effectively and prioritize tasks to align with business objectives.</li>
<li><b>Stakeholder Communication:</b> Serve as the primary point of contact between your team and the group lead. Communicate progress, challenges, and insights clearly and effectively, ensuring alignment with broader organizational goals.</li>
<li><b>MLOps &amp; System Integration:</b> Lead efforts to maintain and enhance the data science infrastructure, integrating new technologies and practices into our workflows. Ensure that models are robust, scalable, and maintainable.</li>
<li><b>Strategic Data Collection:</b> Oversee initiatives to develop and implement data collection strategies that support advanced analytics and model development. Ensure that data pipelines are efficient and reliable.</li>
</ul>
<p><b>What We're Looking For:</b></p>
<ul>
<li><b>7+ Years of Experience:</b> A minimum of 7 years of experience in data science, with at least<b> 2 years in a leadership or managerial role</b>. Demonstrated experience in leading teams and delivering complex data-driven solutions.</li>
<li><b>Expertise in Python:</b> Extensive experience in developing and deploying production-level code in<b> Python, with a deep understanding of machine learning frameworks such as Scikit-learn, PyTorch, TensorFlow</b>, or similar.</li>
<li><b>Strong SQL and Database Knowledge:</b> Proficiency in working with relational databases, writing optimized <b>SQL queries</b>, and managing large-scale datasets.</li>
<li><b>Comprehensive ML Lifecycle Experience:</b> Proven ability to manage the entire lifecycle of <b>ML model development</b>, from ideation and experimentation to deployment and monitoring in a production environment.</li>
<li><b>Analytical &amp; Strategic Thinking:</b> Ability to analyze complex data sets, derive actionable insights, and communicate these insights effectively to both technical and non-technical stakeholders.</li>
<li><b>Educational Background:</b> A Master's or Ph.D. in Statistics, Computer Science, Engineering, or a related quantitative field is preferred.</li>
<li><b>Proven Leadership Skills:</b> Demonstrated ability to lead a team, manage multiple priorities, and work effectively across functions and geographies.</li>
</ul>
<p><b>Bonus Points:</b></p>
<ul>
<li><b>Cross-Functional Collaboration:</b> Experience working with Data/MLOps Engineering, Analytics, Business, and Product teams in a collaborative environment.</li>
<li><b>Domain Specialization:</b> Expertise in areas like fraud detection, credit risk prediction, or graph models and analytics.</li>
<li><b>MLOps &amp; Cloud Infrastructure:</b> Hands-on experience with MLOps, particularly within the AWS ecosystem, and familiarity with orchestration tools like Apache Airflow.</li>
<li><b>Experimentation &amp; Impact Analysis:</b> Skilled in designing experiments and analyzing their outcomes to measure the impact and effectiveness of data-driven solutions.</li>
</ul><div><p><b>
Benefits &amp; Perks</b></p>
<ul>
<li>Excellent group health coverage and life insurance</li>
<li>Stock options</li>
<li>Hybrid work model</li>
<li>Meal allowance</li>
<li>Transportation assistance (terms and conditions apply)</li>
<li>Generous paid time off plan, Holidays</li>
<li>Company-sponsored mental health benefits</li>
<li>Financial advisory services for both short- and long-term goals</li>
<li>Learning and development opportunities to support career growth</li>
<li>Community-based volunteering opportunities</li></ul></div></div>

Manager, Data Science

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