data science lead

Thomas Ren Associates Ltd

<div>
 
 
 Enterprise Data Science Lead &ndash; Applied AI (Corporate Finance)
 
 
 
 
 Location:
 
 Abu Dhabi, UAE |
 
 Full-time
 
 
 
 Are you passionate about transforming finance through AI? A leading Financial Institution is looking for an experienced
 
 Enterprise Data Science Lead
 
 to drive applied AI initiatives within its Corporate Finance division.
 
 
 This is a high-impact role for someone who thrives at the intersection of cutting-edge technology and strategic business outcomes.
 
 
 
 
 
 
 What You&rsquo;ll Do
 
 
 <ul>
 <li>
 Build and deploy AI/ML models to optimize financial decision-making and operations.
 </li>
 <li>
 Develop domain-specific LLMs and RAG pipelines for intelligent automation.
 </li>
 <li>
 Collaborate with Finance, Risk, and Tech teams to identify and deliver AI opportunities.
 </li>
 <li>
 Automate workflows using agent-based AI tools.
 </li>
 <li>
 Evaluate and integrate third-party AI solutions.
 </li>
 <li>
 Champion responsible AI practices (bias detection, explainability, compliance).
 </li>
 </ul>
 
 
 
 
 
 What You Bring
 
 
 <ul>
 <li>
 Master&rsquo;s or PhD in a technical field (CS, Math, Engineering).
 </li>
 <li>
 10&ndash;12 years in applied data science or AI/ML delivery.
 </li>
 <li>
 Hands-on experience with LLM frameworks (LangChain, HuggingFace, Azure OpenAI).
 </li>
 <li>
 Strong MLOps background (CI/CD, monitoring, testing).
 </li>
 <li>
 Excellent communication and stakeholder engagement skills.
 </li>
 </ul>
 
 
 
 
 
 Tech Stack &amp; Tools
 
 
 
 Python | PyTorch | TensorFlow | LangChain | FAISS | Pinecone
 
 
 Azure ML | Snowflake | Airflow | MLflow | SHAP | LIME
 
 
 
 
 
 This role reports to the
 
 Chief Data Analytics Officer
 
 .
 
 
 
 
 
 
 Why Join?
 
 
 <ul>
 <li>
 Lead transformative AI initiatives in a dynamic finance environment.
 </li>
 <li>
 Collaborate with top-tier professionals across disciplines.
 </li>
 <li>
 Competitive compensation and benefits.
 </li>
 <li>
 Shape the future of AI in corporate finance.
 </li>
 </ul>
 
 
 
 
 
 Interested or know someone who fits the bill?
 
 
 
 Let&rsquo;s connect! Drop your CV or tag someone in the comments.
 
 
 
 AIJobs #DataScience #LLM #FinanceCareers #MLOps #Hiring #AbuDhabiJobs #TechLeadership #AppliedAI #CorporateFinance
 
 
</div>

Data Science Specialist

The Entertainer FZ LLC

<div>About Us 
 
The ENTERTAINER is a leading digital company dedicated to adding value for consumers by bringing them the best incentive offers globally. We are a 100% digital, data-driven tech company providing first-rate offers across renowned dining, leisure, entertainment, and hotel brands worldwide. The ENTERTAINER has grown with the aim of creating unbeatable value and loyalty everywhere we operate. We believe that &quot;experience is everything,&quot; and that's why we are passionate about creating unforgettable experiences for our customers, partners, and employees. 
 
About the Role 
 
We are looking for a strategic and hands-on Data Scientist to lead data innovation and decision science within our B2C business. This role will collaborate closely with Product, Technology, Marketing, and Sales teams to develop predictive models, personalization strategies, and business insights that accelerate user acquisition, improve customer retention, and boost merchant engagement &mdash; including voucher redemptions and Digital Reach monetization. 
 
As a Data Scientist you will 
 
Strategic Impact &amp; Business Influence<ul><li>
Define and execute a holistic data science strategy aligned with B2C growth goals.</li><li>
Drive experimentation and insight generation to optimize key levers: user engagement, subscription renewals, merchant redemptions, and DR visibility.</li><li>
Influence key decisions across marketing campaigns, product features and merchant onboarding through predictive insights.</li><li>
Serve as a data evangelist, promoting cross-functional alignment and a strong data-first mindset.</li><li>
Stay ahead of AI/ML advancements and implement cutting-edge techniques to solve business challenges.
</li></ul> 
Product &amp; Business Intelligence<ul><li>
Build churn prediction models, lifetime value (LTV) scoring, and behavioral segmentation to enhance subscription lifecycle management.</li><li>
Analyze in-app behavior and transaction data to optimize Digital Reach placement effectiveness and merchant ROI.</li><li>
Collaborate with Product teams to implement A/B testing frameworks and data-backed roadmap prioritization.</li><li>
Build customer segmentation models to personalize offers, improve targeting, and enhance loyalty program effectiveness.</li><li>
Work with Marketing to optimize customer acquisition costs (CAC), churn prediction, and retention strategies.</li><li>
Support Sales &amp; Partnerships with merchant performance analytics to drive higher voucher redemptions and upsell opportunities.</li><li>
Implement real-time analytics dashboards to track KPIs (active users, redemptions, DR revenue) and provide actionable insights.
</li></ul> 
Analytics Engineering &amp; Infrastructure<ul><li>
Partner with Data Engineers to build scalable data pipelines and maintain a clean data lake suitable for advanced analytics.</li><li>
Lead development of dashboards and self-serve analytics tools for key stakeholders.</li></ul> 

What we&rsquo;re looking for<ul><li>
3-5 years of experience in Data Science, Machine Learning or Advanced Analytics, ideally in a B2C e-commerce, subscription or digital commerce environment.</li><li>
Bachelor's or Master&rsquo;s degree in Computer Science, Statistics, Mathematics, Data Science, or a related field.</li><li>
Proficiency in Python, R, SQL, and Big Data platforms such as BigQuery, MLFlow, Databricks, GCP, or AWS.</li><li>
Deep understanding of machine learning (e.g., XGBoost, LightGBM, Scikit-learn) and predictive modeling techniques.</li><li>
Proficiency in designing experiments (A/B testing) and statistical inference techniques.</li></ul> 

Preferred:<ul><li>
Experience working on mobile app analytics, offer redemption behavior, or consumer loyalty ecosystems.</li><li>
Exposure to advertising analytics and performance optimization for in-app marketing/ads (like DR).</li><li>
Familiarity with modern data visualization tools like Tableau, Power BI.</li></ul> 

Core Competencies<ul><li>
Strategic thinker with strong business acumen and the ability to translate data into commercial impact.</li><li>
Excellent communication and storytelling skills to influence executive stakeholders.</li><li>
Track record of delivering high-impact insights and building analytics capabilities from scratch.</li><li>
Strong mentoring, coaching, and cross-functional collaboration abilities.</li></ul> 

What We Offer<ul><li>
Competitive salary and benefits package.</li><li>
Opportunity to work with an energetic and innovative company.</li><li>
A chance to contribute to the success of a well-known UAE brand.</li></ul>
AdJwLsSZTb</div>

Data Scientist

Enable Data

Enable Data Incorporated is looking for a talented and experienced Lead Data Scientist to join our innovative team. In this role, you will be responsible for driving data science initiatives, developing predictive models, and providing insights that guide key business decisions. The ideal candidate has a strong background in statistical analysis, machine learning, and big data technologies, and is enthusiastic about applying data-driven solutions to complex business problems.
 As the Lead Data Scientist, you will collaborate closely with cross-functional teams, including engineering, product management, and business stakeholders. You will leverage your expertise to design and implement advanced analytics solutions that optimize our clients’ operations and enhance their product offerings.
 This is an exciting opportunity for a pro-active leader with a passion for data science and a proven track record of delivering impactful results.
 
Requirements: 
Required qualifications: 
<ul>
<li>7+ years of experience in data science or a related field, with a strong emphasis on machine learning and predictive modeling.</li>
<li>Proficiency in programming languages such as Python</li>
<li>Deep understanding of statistical analysis, machine learning algorithms, and data mining techniques</li>
<li>Classical Machine Learning, Statistical analysis and and Data Science</li>
<li>Hospitality experience (preferred)</li>
<li>Python libraries like Pandas, Numpy, scikit-learn, TensorFlow, Keras</li>
<li>Practical experience with Databricks</li>
<li>SQL proficiency</li>
<li>Generative AI solutions (and fine tuning) utilizing LLMs such as GPT, Claude, and LLaMA</li>
<li>Libraries such as LangChain, Transformers, OpenAI SDK, or Hugging Face</li>
</ul>

Lead Data Scientist

Hays

<div>
 
 
 Lead Data Scientist
 
 
 
 
 
 
 About the Role:
 
 
 
 
 
 We&rsquo;re looking for a dynamic Lead Data Scientist to drive end-to-end delivery of impactful AI and data science solutions. You&rsquo;ll lead a small, high-performing team, work closely with senior stakeholders, and champion data-driven decision-making across the business. This is a hands-on leadership role ideal for someone with a fintech or start-up background who thrives in fast-paced, agile environments.
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 <ul>
 <li>
 Lead and mentor a team of data scientists, fostering a collaborative and innovative culture.
 </li>
 <li>
 Own delivery of AI/ML projects from ideation to deployment.
 </li>
 <li>
 Engage with senior stakeholders to align data initiatives with business goals.
 </li>
 <li>
 Identify and develop high-impact use cases across functions (Ops, Marketing, Finance).
 </li>
 <li>
 Drive agile, iterative development and ensure timely, high-quality execution.
 </li>
 </ul>
 
 
 
 
 What You&rsquo;ll Bring:
 
 
 
 
 <ul>
 <li>
 8+ years of experience in data science, with 2+ years in a leadership role.
 </li>
 <li>
 Proven track record of delivering end-to-end AI/ML solutions.
 </li>
 <li>
 Strong stakeholder management and communication skills.
 </li>
 <li>
 Experience in fintech or start-up environments preferred.
 </li>
 <li>
 Proficiency in Python, SQL, and modern ML frameworks.
 </li>
 <li>
 Wholesome data science experience (LLM&rsquo;s, AI automation, GenAI, advanced analytics)
 </li>
 <li>
 Quantitative finance implementation (desired)
 </li>
 </ul>
</div>

Uber

<div>
 
 About The Team
 
 
 
 Ever wondered how Uber makes it seamless to hail an auto or bike taxi in the middle of rush hour, or how pricing works for your next metered cab ride? That's the kind of real-world complexity the Hailables Science team thrives on solving.
 
 
 As part of Uber's Core Analytics &amp; Science (CAS) organization, the Hailables team focuses on our fastest-growing Mobility offerings, which include auto rickshaws, bike taxis, and metered cabs. These products operate in high-density, price-sensitive markets with unique customer behaviors and regulatory landscapes. We offer a rare opportunity to work at the frontier of data science in this space.
 
 
 We partner closely with product, engineering, and operations teams to design smarter systems. It ranges from more intelligent pricing systems, efficient matching algorithms, and building personalized experience for millions of riders and drivers across emerging markets. From improving pickup reliability to shaping how supply and demand interact in highly dynamic cities, the Hailables team is where science meets street-level scale.
 
 
 
 About The Role
 
 
 
 As the Science Tech Lead (Individual Contributor) for the Hailables charter, you'll be at the heart of product development, guiding the science direction for a team of 5-7 talented scientists based in India. You'll work closely with Engineering and Product partners to define strategy, shape roadmaps, and drive execution. You will bring data, algorithms, and business context together to solve complex, real-world problems.
 
 
 In this role, you won't just influence - you'll build. Whether it's designing machine learning models to improve matching and pricing, uncovering insights through rigorous experimentation, or applying statistical thinking to shape product levers, you'll lead by example. You'll also mentor team members, foster a culture of scientific excellence, and build strong cross-functional relationships with global stakeholders across time zones.
 
 
 This is a rare opportunity to lead from the front: as a senior IC, you'll own the scientific vision while staying hands-on, solving meaningful problems that impact millions of users across Uber's fastest-growing mobility products.
 
 
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 Undergraduate and/or graduate degree in Statistics, Machine Learning, Operations Research, or other quantitative fields.
 </li>
 <li>
 9+ years of industry experience as an (Applied / Data) Scientist or equivalent.
 </li>
 <li>
 Experience with exploratory data analysis, statistical analysis and testing, causal analysis and ML model development.
 </li>
 <li>
 Experience in experimental design and analysis.
 </li>
 <li>
 Proficiency using Python, Spark at scale with large data sets.
 </li>
 <li>
 Experience with tools like SQL, R in a production environment.
 
 
 </li>
 </ul>
 
 
 Preferred Qualifications
 
 
 
 
 <ul>
 <li>
 Master's/Ph.D. Degree in Statistics, Machine Learning, Operations Research, or other quantitative fields.
 </li>
 <li>
 Experience in tech or marketplace industries.
 </li>
 <li>
 Experienced in partnering with cross-functional stakeholders to execute decisions.
 </li>
 <li>
 Ability to mentor, coach and develop junior team members.
 </li>
 <li>
 Superb communication and organisation skills.
 
 
 </li>
 </ul>
 
 What the candidate will do
 
 
 
 <ul>
 <li>
 Define the science roadmap in collaboration with Product and Engineering, identifying key opportunities to improve rider and driver experience across autos, bike taxis, and metered cabs.
 </li>
 <li>
 Design and prototype machine learning and statistical solutions to solve core marketplace challenges like pricing, matching, and user funnel optimization.
 </li>
 <li>
 Lead experimentation efforts (A/B, switchback, quasi-experiments), ensuring methodological rigor and high-quality insights.
 </li>
 <li>
 Define and monitor key tech OKRs, ensuring the right metrics are in place and tracked accurately to guide product and engineering execution.
 </li>
 <li>
 Improve data quality, observability, and reliability by partnering with Engineering on logging, metrics, and pipelines.
 </li>
 <li>
 Conduct deep-dive analyses to generate actionable insights and influence product direction.
 </li>
 <li>
 Mentor scientists and promote a culture of excellence in modeling, experimentation, and analytics.
 </li>
 <li>
 Communicate scientific work and outcomes clearly to cross-functional stakeholders and leadership.
 </li>
 </ul>
</div>

Staff Scientist, Tech

AstraZeneca

<div><h2 class="jobSectionHeader">Job Title: AI Engineering Specialist - Level 1</h2>
Introduction to role:
Are you ready to make a significant impact in the world of healthcare? We are seeking a Senior Data Scientist to lead our Data Science and AI initiatives within AstraZeneca's Commercial Data Science &amp; AI Team, located in Chennai and Bangalore, India. Collaborate with business and medical experts across various disease areas, brands, and indications to harness the power of machine learning, natural language processing, foundational models, and knowledge graphs. Your work will support the commercialization of new medicines, transforming healthcare delivery and improving the lives of millions globally. Join a global team dedicated to advancing data science tools that revolutionize patient care.<h2 class="jobSectionHeader">
Accountabilities:</h2><ul><li>
Build, develop, and lead a team of high-performing Data Scientists.</li><li>
Coordinate with cross-functional teams including Data Science &amp; AI, Commercial, Medical, and IT globally.</li><li>
Research and apply the latest ML algorithms with a focus on Generative AI techniques for content creation and data augmentation.</li><li>
Apply ML models, feature engineering, and interpret model outcomes for business stakeholders.</li><li>
Integrate structured and unstructured data into knowledge bases.</li><li>
Design and create AZ knowledge graph.</li><li>
Collaborate with data teams to demonstrate data science for research questions.</li><li>
Partner with Commercial teams to build scalable data science solutions using Generative AI.</li><li>
Drive collaborations with local data science companies.</li><li>
Integrate data to build personalized patient journeys using LLMs and Diffusion Models.</li><li>
Fine-tune LLMs and vision models for commercial problems.</li><li>
Develop strategies for responsible use of Generative AI, including bias detection.</li><li>
Optimize LLM performance through prompt engineering techniques.</li></ul><h2 class="jobSectionHeader">
Essential Skills/Experience:</h2><ul><li>
BS (or equivalent experience) in mathematics, computer science, engineering, physics, statistics, computational sciences, or related quantitative discipline.</li><li>
Approximately 8-10 years of experience in core ML and AI projects.</li><li>
Prior experience/understanding with 3-5 years' experience in foundational tools.</li><li>
Mandatory Technical Skills: Python, Jupyter notebook, Scikit-learn, SQL, StreamLit, Amazon Bedrock, Jumpstart, OpenAI, Langchain, LlamaIndex. Good knowledge of cloud platforms (GCP, Azure, AWS).</li><li>
Deep Learning tools: Pytorch/Tensorflow, HuggingFace.</li><li>
Machine Learning: Classical methods including classification and regression algorithms like k-means clustering, support vector machines, random forests.</li><li>
Deep Learning: Fully Connected Architecture, Convolutional Networks, RNN/LSTM. In-depth knowledge of LLMs like GPT, Claude, Gemini, Falcon, LLAMA. Large pre-trained image models like Inception, Mobilenet, YOLO; generative image models like Stable Diffusion.</li><li>
Generative AI: Experience with models/frameworks for text generation, image synthesis, data augmentation.</li><li>
Prompt Engineering: Ability to design and optimize prompts for LLMs.</li></ul><h2 class="jobSectionHeader">
Desirable Skills/Experience:</h2><ul><li>
Master or PhD in ML or Computer Science in mathematics, computer science, engineering, physics, statistics, computational sciences.</li><li>
Experience working on structured/unstructured data problems in data science.</li><li>
Track record of independently leading data science projects for business/scientific problems.</li><li>
Exceptional skills in Python.</li><li>
Familiarity with database systems like SQL and NoSQL.</li><li>
Coaching and nurturing junior Data Scientists.</li><li>
Pipeline Tools: Airflow/Luigi, MLFlow, Great Expectations.</li><li>
ML Production Tools: Docker, Kubeflow (Familiarity and desire to learn).</li><li>
Reinforcement Learning.</li><li>
Experience with Vector Databases (e.g., Pinecone, Weaviate).</li><li>
Knowledge of MLOps practices for deploying/monitoring Generative AI models.</li><li>
Familiarity with ethical considerations in AI.</li></ul>
When we put unexpected teams in the same room, we ignite 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.
At AstraZeneca, we are driven by a bold ambition to eliminate cancer as a cause of death. Our dynamic environment fosters collaboration among the brightest minds who work side by side to make impactful advances. With a growth mindset and a commitment to innovation, we harness diverse expertise to transform patient care. Our ambitious spirit encourages stepping out of comfort zones to lead changes in an ever-evolving landscape. Join us to be part of a team that is reshaping healthcare systems through collaboration and advocacy.
Ready to make a difference? Apply now and be part of our journey to transform healthcare!</div>

AI Engineering Specialist - Level 1

Honeywell

<div>We are seeking a seasoned Lead Data Scientist to spearhead data-driven innovation in the industrial and buildings domain. This role involves leading a team to develop advanced analytics and machine learning solutions that optimize building operations, enhance energy efficiency, and enable predictive maintenance across industrial assets and smart infrastructure.</div>
 <div><h3 class="jobSectionHeader">Strategic Leadership
</h3><ul><li>Define and execute the data science strategy for smart buildings and industrial systems.
</li><li>Collaborate with engineering, product, and operations teams to align analytics initiatives with business and sustainability goals.
</li><li>Drive adoption of AI/ML solutions across building automation, HVAC systems, energy management, and asset monitoring.
</li></ul><h3 class="jobSectionHeader">Advanced Analytics &amp; Modeling
</h3><ul><li>Develop predictive models for equipment failure, energy consumption forecasting, and occupant behavior analysis.
</li><li>Apply time-series analysis, anomaly detection, and optimization algorithms to real-time sensor and IoT data.
</li><li>Leverage geospatial and environmental data to improve building performance and safety.
</li></ul><h3 class="jobSectionHeader">Project &amp; Team Management
</h3><ul><li>Lead cross-functional data science projects from ideation to deployment.
</li><li>Mentor junior data scientists and foster a culture of experimentation and continuous improvement.
</li><li>Ensure robust model validation, documentation, and compliance with industry standards.
</li></ul><h3 class="jobSectionHeader">Stakeholder Engagement
</h3><ul><li>Translate complex analytical insights into actionable recommendations for facility managers, engineers, and business leaders.
</li><li>Build intuitive dashboards and visualizations to monitor KPIs like energy usage, equipment health, and operational efficiency. 
</li></ul><h3 class="jobSectionHeader">Machine Learning &amp; AI
</h3><ul><li>Supervised and unsupervised learning
</li><li>Deep learning (CNNs, RNNs, transformers)
</li><li>Reinforcement learning for control systems
</li></ul><h3 class="jobSectionHeader">Statistical Analysis &amp; Modeling
</h3><ul><li>Regression, classification, clustering
</li><li>Time-series forecasting and anomaly detection
</li><li>Bayesian inference and probabilistic modeling
</li></ul><h3 class="jobSectionHeader">Programming &amp; Tools
</h3><ul><li>Python, R, SQL
</li><li>Libraries: scikit-learn, TensorFlow, PyTorch, XGBoost, Statsmodels
</li><li>Data manipulation: Pandas, NumPy, Dask
</li></ul><h3 class="jobSectionHeader">Big Data &amp; Cloud Platforms
</h3><ul><li>Spark, Hadoop, Kafka
</li><li>AWS, Azure, GCP (especially IoT and analytics services)
</li></ul><h3 class="jobSectionHeader">Data Visualization &amp; BI
</h3><ul><li>Dash, Plotly, Matplotlib, Seaborn
</li><li>Power BI, Tableau, Grafana
</li></ul><h3 class="jobSectionHeader">MLOps &amp; Deployment
</h3><ul><li>Model versioning, CI/CD pipelines
</li><li>Docker, Kubernetes, MLflow
</li><li>Integration with BMS and industrial control systems
</li></ul><h3 class="jobSectionHeader">Domain-Specific Expertise
</h3><ul><li>Sensor fusion and IoT analytics
</li><li>Building automation protocols (BACnet, Modbus)
</li><li>Energy modeling and sustainability metrics</li></ul></div>
 <div><ul><li>Master&rsquo;s or Ph.D. in Data Science, Engineering, Statistics, or a related field.
</li><li>7+ years of experience in data science, with at least 2 years in a leadership role.
</li><li>Proven experience in industrial or smart building environments.
</li><li>Strong communication and stakeholder management skills.</li></ul></div>
 <div>Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments &ndash; powered by our Honeywell Forge software &ndash; that help make the world smarter, safer and more sustainable.</div>

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